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Fulltext Local convexity-preserving C2 rational cubic spline for convex data

Abbas M, Abd Majid A, Ali JM

ScientificWorldJournal, 2014;2014:391568.
PMID: 24757421 DOI: 10.1155/2014/391568

We present the smooth and visually pleasant display of 2D data when it is convex, which is contribution towards the improvements over existing methods. This improvement can be used to get the more accurate results. An attempt has been made in order to develop the local convexity-preserving interpolant for convex data using C(2) rational cubic spline. It involves three families of shape parameters in its representation. Data dependent sufficient constraints are imposed on single shape parameter to conserve the inherited shape feature of data. Remaining two of these shape parameters are used for the modification of convex curve to get a visually pleasing curve according to industrial demand. The scheme is tested through several numerical examples, showing that the scheme is local, computationally economical, and visually pleasing.

Matched MeSH terms: Image Enhancement/methods
A knowledge interaction learning for multi-echo MRI motion artifact correction towards better enhancement of SWI

Al-Masni MA, Lee S, Al-Shamiri AK, Gho SM, Choi YH, Kim DH

Comput Biol Med, 2023 Feb;153:106553.
PMID: 36641933 DOI: 10.1016/j.compbiomed.2023.106553

Patient movement during Magnetic Resonance Imaging (MRI) scan can cause severe degradation of image quality. In Susceptibility Weighted Imaging (SWI), several echoes are typically measured during a single repetition period, where the earliest echoes show less contrast between various tissues, while the later echoes are more susceptible to artifacts and signal dropout. In this paper, we propose a knowledge interaction paradigm that jointly learns feature details from multiple distorted echoes by sharing their knowledge with unified training parameters, thereby simultaneously reducing motion artifacts of all echoes. This is accomplished by developing a new scheme that boosts a Single Encoder with Multiple Decoders (SEMD), which assures that the generated features not only get fused but also learned together. We called the proposed method Knowledge Interaction Learning between Multi-Echo data (KIL-ME-based SEMD). The proposed KIL-ME-based SEMD allows to share information and gain an understanding of the correlations between the multiple echoes. The main purpose of this work is to correct the motion artifacts and maintain image quality and structure details of all motion-corrupted echoes towards generating high-resolution susceptibility enhanced contrast images, i.e., SWI, using a weighted average of multi-echo motion-corrected acquisitions. We also compare various potential strategies that might be used to address the problem of reducing artifacts in multi-echoes data. The experimental results demonstrate the feasibility and effectiveness of the proposed method, reducing the severity of motion artifacts and improving the overall clinical image quality of all echoes with their associated SWI maps. Significant improvement of image quality is observed using both motion-simulated test data and actual volunteer data with various motion severity strengths. Eventually, by enhancing the overall image quality, the proposed network can increase the effectiveness of the physicians' capability to evaluate and correctly diagnose brain MR images.

Matched MeSH terms: Image Enhancement/methods
Comparison study of the MRI shoulder PROPELLER technique with differential image quality by variation of shoulder coils

Khairi M, Zakaria F, Supar R, Mohd Z

Med J Malaysia, 2024 Mar;79(Suppl 1):74-81.
PMID: 38555889

INTRODUCTION: Motion and pulsation artifacts are the most prominent types of artifacts in Magnetic Resonance Imaging (MRI) of the shoulder. Therefore, this study examined the Periodically Rotating Overlapping Parallel Lines with Enhanced Reconstruction (PROPELLER) technique with small flex coil (SFC) and dedicated shoulder coil (DSC) for the reduction of motion and pulsation artifacts. The signalto- noise ratio (SNR) and contrast-to-noise ratio (CNR) of the standard proton density fat saturation (PDFS) pulse sequence and the PROPELLER proton density fat saturation (PROPELLER PDFS) pulse sequence were also evaluated.
MATERIALS AND METHODS: Eighteen (18) participants who met the inclusion and exclusion criteria were scanned using a standard non-contrast MRI shoulder protocol including the PDFS pulse sequence and the PROPELLER PDFS pulse sequence using a small flex coil and a dedicated shoulder coil. Two experienced musculoskeletal (MSK) radiologists evaluated and graded the presence of artifacts on the MR images and the SNR and CNR were measured quantitatively.
RESULTS: The non-parametric Wilcoxon Signed Rank test revealed a significant reduction in motion and pulsation artifacts between the PROPELLER PDFS pulse sequence and the standard PDFS pulse sequence. In addition, the nonparametric Mann-Whitney U test revealed that the mean rank of SNR for the standard sequence was statistically significant when compared to the PROPELLER sequence for both coil types. The CNR of the PROPELLER sequence was statistically significant between fat-fluid, bone-fluid, bonetendon, bone-muscle, and muscle-fluid when using SFC and DSC.
CONCLUSION: This study proved that the PROPELLER-PDFS pulse sequence effectively eliminates motion and pulsation artifacts, regardless of the coils utilised. The PROPELLERPDFS pulse sequence can therefore be implemented into the standard MRI shoulder procedure.

Matched MeSH terms: Image Enhancement/methods
Fulltext Subspace-based technique for speckle noise reduction in ultrasound images

Yahya N, Kamel NS, Malik AS

Biomed Eng Online, 2014;13(1):154.
PMID: 25421914 DOI: 10.1186/1475-925X-13-154

Ultrasound imaging is a very essential technique in medical diagnosis due to its being safe, economical and non-invasive nature. Despite its popularity, the US images, however, are corrupted with speckle noise, which reduces US images qualities, hampering image interpretation and processing stage. Hence, there are many efforts made by researches to formulate various despeckling methods for speckle reduction in US images.

Matched MeSH terms: Image Enhancement/methods*
A comparison of wavelet and curvelet for breast cancer diagnosis in digital mammogram

Meselhy Eltoukhy M, Faye I, Belhaouari Samir B

Comput Biol Med, 2010 Apr;40(4):384-91.
PMID: 20163793 DOI: 10.1016/j.compbiomed.2010.02.002

This paper presents a comparative study between wavelet and curvelet transform for breast cancer diagnosis in digital mammogram. Using multiresolution analysis, mammogram images are decomposed into different resolution levels, which are sensitive to different frequency bands. A set of the biggest coefficients from each decomposition level is extracted. Then a supervised classifier system based on Euclidian distance is constructed. The performance of the classifier is evaluated using a 2 x 5-fold cross validation followed by a statistical analysis. The experimental results suggest that curvelet transform outperforms wavelet transform and the difference is statistically significant.

Matched MeSH terms: Image Enhancement/methods*
Time-domain reconstruction using sensitivity coefficients for limited view ultrawide band tomography

Abdullah MZ, Yin W, Bilal M, Armitage DW, Mackin R, Peyton AJ

Rev Sci Instrum, 2007 Aug;78(8):084703.
PMID: 17764343

This article addresses time-domain ultrawide band (UWB) electromagnetic tomography for reconstructing the unknown spatial characteristic of an object from observations of the arrivals of short electromagnetic (EM) pulses. Here, the determination of the first peak arrival of the EM traces constitutes the forward problem, and the inverse problem aims to reconstruct the EM property distribution of the media. In this article, the finite-difference time-domain method implementing a perfectly matched layer is used to solve the forward problem from which the system sensitivity maps are determined. Image reconstruction is based on the combination of a linearized update and regularized Landweber minimization algorithm. Experimental data from a laboratory UWB system using targets of different contrasts, sizes, and shapes in an aqueous media are presented. The results show that this technique can accurately detect and locate unknown targets in spite of the presence of significant levels of noise in the data.

Matched MeSH terms: Image Enhancement/methods*
Magnetic resonance angiographic demonstration of carotid-cavernous fistula using elliptical centric time resolved imaging of contrast kinetics (EC-TRICKS)

Vattoth S, Cherian J, Pandey T

Magn Reson Imaging, 2007 Oct;25(8):1227-31.
PMID: 17442526

Magnetic resonance angiographic evaluation of the intracranial vasculature has been predominantly carried out using conventional angiographic techniques such as time of flight and phase contrast sequences. These techniques have good spatial resolution but lack temporal resolution. Newer faster angiographic techniques have been developed to circumvent this limitation. Elliptical centric time-resolved imaging of contrast kinetics (EC-TRICKS) is one such technique which has combined the use of elliptical centric ordering of the k-space with multiphase 3D digital subtraction MR angiogram (MRA) to achieve excellent temporal resolution of the arterial and venous circulations. Its applications have been mainly in the peripheral vasculature. We report the use of this technique in a case of a high-flow, direct carotid-cavernous fistula to demonstrate its potential in intracranial MR angiography.

Matched MeSH terms: Image Enhancement/methods*
Neural networks aided stone detection in thick slab MRCP images

Logeswaran R

Med Biol Eng Comput, 2006 Aug;44(8):711-9.
PMID: 16937213

This paper proposes a detection scheme for identifying stones in the biliary tract of the body, which is examined using magnetic resonance cholangiopancreatography (MRCP), a sequence of magnetic resonance imaging targeted at the pancreatobiliary region of the abdomen. The scheme enhances the raw 2D thick slab MRCP images and extracts the biliary structure in the images using a segment-based region-growing approach. Detection of stones is scoped within this extracted structure, by highlighting possible stones. A trained feedforward artificial neural network uses selected features of size and average segment intensity as its input to detect possible stones in MRCP images and eliminate false stone-like objects. The proposed scheme achieved satisfactory results in tests of clinical MRCP thick slab images, indicating potential for implementation in computer-aided diagnosis systems for the liver.

Matched MeSH terms: Radiographic Image Enhancement/methods
Enhancement of seminal stains using background correction algorithm with colour filters

Lee WC, Khoo BE, Abdullah AFL

Forensic Sci Int, 2016 06;263:1-9.
PMID: 27061146 DOI: 10.1016/j.forsciint.2016.03.046

Evidence in crime scenes available in the form of biological stains which cannot be visualized during naked eye examination can be detected by imaging their fluorescence using a combination of excitation lights and suitable filters. These combinations selectively allow the passage of fluorescence light emitted from the targeted stains. However, interference from the fluorescence generated by many of the surface materials bearing the stains often renders it difficult to visualize the stains during forensic photography. This report describes the use of background correction algorithm (BCA) to enhance the visibility of seminal stain, a biological evidence that fluoresces. While earlier reports described the use of narrow band-pass filters for other fluorescing evidences, here, we utilize BCA to enhance images captured using commonly available colour filters, yellow, orange and red. Mean-based contrast adjustment was incorporated into BCA to adjust the background brightness for achieving similarity of images' background appearance, a crucial step for ensuring success while implementing BCA. Experiment results demonstrated the effectiveness of our proposed colour filters' approach using the improved BCA in enhancing the visibility of seminal stains in varying dilutions on selected surfaces.

Matched MeSH terms: Image Enhancement/methods*
Fulltext Hybrid Pixel-Based Method for Cardiac Ultrasound Fusion Based on Integration of PCA and DWT

Mazaheri S, Sulaiman PS, Wirza R, Dimon MZ, Khalid F, Moosavi Tayebi R

Comput Math Methods Med, 2015;2015:486532.
PMID: 26089965 DOI: 10.1155/2015/486532

Medical image fusion is the procedure of combining several images from one or multiple imaging modalities. In spite of numerous attempts in direction of automation ventricle segmentation and tracking in echocardiography, due to low quality images with missing anatomical details or speckle noises and restricted field of view, this problem is a challenging task. This paper presents a fusion method which particularly intends to increase the segment-ability of echocardiography features such as endocardial and improving the image contrast. In addition, it tries to expand the field of view, decreasing impact of noise and artifacts and enhancing the signal to noise ratio of the echo images. The proposed algorithm weights the image information regarding an integration feature between all the overlapping images, by using a combination of principal component analysis and discrete wavelet transform. For evaluation, a comparison has been done between results of some well-known techniques and the proposed method. Also, different metrics are implemented to evaluate the performance of proposed algorithm. It has been concluded that the presented pixel-based method based on the integration of PCA and DWT has the best result for the segment-ability of cardiac ultrasound images and better performance in all metrics.

Matched MeSH terms: Image Enhancement/methods*
Evaluating the quality of images produced by soft X-ray units

Bradley DA, Wong CS, Ng KH

Appl Radiat Isot, 2000 9 26;53(4-5):691-7.
PMID: 11003508

For broad-beam soft X-ray sources, assessment of the quality of image produced by such units is made complex by the low penetration capabilities of the radiation. In the present study we have tested the utility of several types of test tool, some of which have been fabricated by us, as part of an effort to evaluate several key image defining parameters. These include the film characteristic, focal-spot size, image resolution and detail detectability. The two sources of X-rays used in present studies were the University of Malaya flash X-ray device (UMFX1) and a more conventional soft X-ray tube (Softex, Tokyo), the latter operating at peak accelerating potentials of 20 kVp. We have established, for thin objects, that both systems produce images of comparable quality and, in particular, objects can be resolved down to better than 45 microm.

Matched MeSH terms: Radiographic Image Enhancement/methods*
A fuzzy-based texture analysis for tissue characterization of diffused liver diseases on B-scan images

Gangeh MJ, Hanmandlu M, Bister M

Biomed Sci Instrum, 2002;38:369-74.
PMID: 12085634

The specific texture on B-scan images is believed to be related to both ultrasound machine characteristics and tissue properties, i.e., the pathological states of the soft tissue. Therefore, for classification, features can be extracted with the use of image texture analysis techniques. In this paper a novel fuzzy approach for texture characterization is used for classification of normal liver and diffused liver diseases, here fatty liver, liver cirrhosis, and hepatitis are emphasized. The texture analysis techniques are diversified by the existence of several approaches. We propose fuzzy features for the analysis of the texture image. For this, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window. Using these membership function values, we find a feature by weighted average method for the current pixel. This is repeated for all pixels in the window treating each time one pixel as the current pixel. Using these fuzzy based features, we derive three descriptors: maximum, entropy, and energy as used in co-occurrence method, for each window.

Matched MeSH terms: Image Enhancement/methods*
A comparative study of computed radiography-based mammography using digital phosphor storage plate and full field digital mammography

Chelliah KK, Tamanang S, Bt Elias LS, Ying KY

Indian J Med Sci, 2013 11 2;67(1-2):23-8.
PMID: 24178338

BACKGROUND: Two digital mammography systems, based on different physical concepts, have been introduced in the last few years namely the full-field digital mammography (FFDM) system and computed radiography-based mammography using digital storage phosphor plate (DSPM).
AIMS: The objective of this study was to compare the image quality for DSPM and FFDM using a grading scale based on previously published articles.
MATERIALS AND METHODS: This comparative diagnostic study was done for 5-month duration at the Breast Clinic. The system used was the Lorad Selenia FFDM system and the Mammomat 3000 Nova DSPM system. The craniocaudal and mediolateral oblique projections were done on both breast on 58 asymptomatic women using both DSPM and FFDM. The mammograms were evaluated for eight criteria of image quality: Tissue coverage, compression, exposure, contrast, resolution, noise, artifact, and sharpness by two independent radiologists.
STATISTICAL ANALYSIS: Wilcoxon Signed Rank Test and Weighted Kappa.
RESULTS: FFDM was rated significantly better (P < 0.05) for five aspects: Tissue coverage, compression, contrast, exposure, and resolution and equal to DSPM for sharpness, noise, and artifact.
CONCLUSION: FFDM was superior in five aspects and equal to DSPM for three aspects of image quality.

Matched MeSH terms: Radiographic Image Enhancement/methods*
A robust background correction algorithm for forensic bloodstain imaging using mean-based contrast adjustment

Lee WC, Khoo BE, Abdullah AFL

Sci Justice, 2016 May;56(3):201-209.
PMID: 27162018 DOI: 10.1016/j.scijus.2016.01.001

Background correction algorithm (BCA) is useful in enhancing the visibility of images captured in crime scenes especially those of untreated bloodstains. Successful implementation of BCA requires all the images to have similar brightness which often proves a problem when using automatic exposure setting in a camera. This paper presents an improved background correction algorithm (BCA) that applies mean-based contrast adjustment as a pre-correction step to adjust the mean brightness of images to be similar before implementing BCA. The proposed modification, namely mean-based adaptive BCA (mABCA) was tested on various image samples captured under different illuminations such as 385 nm, 415 nm and 458 nm. We also evaluated mABCA of two wavelengths (415 nm and 458 nm) and three wavelengths (415 nm, 380 nm and 458 nm) in enhancing untreated bloodstains on different surfaces. The proposed mABCA is found to be more robust in processing images captured in different brightness and thus overcomes the main issue faced in the original BCA.

Matched MeSH terms: Image Enhancement/methods*
Automated pterygium detection method of anterior segment photographed images

Wan Zaki WMD, Mat Daud M, Abdani SR, Hussain A, Mutalib HA

Comput Methods Programs Biomed, 2018 Feb;154:71-78.
PMID: 29249348 DOI: 10.1016/j.cmpb.2017.10.026

BACKGROUND AND BJECTIVE: Pterygium is an ocular disease caused by fibrovascular tissue encroachment onto the corneal region. The tissue may cause vision blurring if it grows into the pupil region. In this study, we propose an automatic detection method to differentiate pterygium from non-pterygium (normal) cases on the basis of frontal eye photographed images, also known as anterior segment photographed images.
METHODS: The pterygium screening system was tested on two normal eye databases (UBIRIS and MILES) and two pterygium databases (Australia Pterygium and Brazil Pterygium). This system comprises four modules: (i) a preprocessing module to enhance the pterygium tissue using HSV-Sigmoid; (ii) a segmentation module to differentiate the corneal region and the pterygium tissue; (iii) a feature extraction module to extract corneal features using circularity ratio, Haralick's circularity, eccentricity, and solidity; and (iv) a classification module to identify the presence or absence of pterygium. System performance was evaluated using support vector machine (SVM) and artificial neural network.
RESULTS: The three-step frame differencing technique was introduced in the corneal segmentation module. The output image successfully covered the region of interest with an average accuracy of 0.9127. The performance of the proposed system using SVM provided the most promising results of 88.7%, 88.3%, and 95.6% for sensitivity, specificity, and area under the curve, respectively.
CONCLUSION: A basic platform for computer-aided pterygium screening was successfully developed using the proposed modules. The proposed system can classify pterygium and non-pterygium cases reasonably well. In our future work, a standard grading system will be developed to identify the severity of pterygium cases. This system is expected to increase the awareness of communities in rural areas on pterygium.

Matched MeSH terms: Image Enhancement/methods*
Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images

Gandhamal A, Talbar S, Gajre S, Hani AF, Kumar D

Comput Biol Med, 2017 04 01;83:120-133.
PMID: 28279861 DOI: 10.1016/j.compbiomed.2017.03.001

Most medical images suffer from inadequate contrast and brightness, which leads to blurred or weak edges (low contrast) between adjacent tissues resulting in poor segmentation and errors in classification of tissues. Thus, contrast enhancement to improve visual information is extremely important in the development of computational approaches for obtaining quantitative measurements from medical images. In this research, a contrast enhancement algorithm that applies gray-level S-curve transformation technique locally in medical images obtained from various modalities is investigated. The S-curve transformation is an extended gray level transformation technique that results into a curve similar to a sigmoid function through a pixel to pixel transformation. This curve essentially increases the difference between minimum and maximum gray values and the image gradient, locally thereby, strengthening edges between adjacent tissues. The performance of the proposed technique is determined by measuring several parameters namely, edge content (improvement in image gradient), enhancement measure (degree of contrast enhancement), absolute mean brightness error (luminance distortion caused by the enhancement), and feature similarity index measure (preservation of the original image features). Based on medical image datasets comprising 1937 images from various modalities such as ultrasound, mammograms, fluorescent images, fundus, X-ray radiographs and MR images, it is found that the local gray-level S-curve transformation outperforms existing techniques in terms of improved contrast and brightness, resulting in clear and strong edges between adjacent tissues. The proposed technique can be used as a preprocessing tool for effective segmentation and classification of tissue structures in medical images.

Matched MeSH terms: Image Enhancement/methods*
Fulltext An efficient post-processing adaptive filtering technique to rectifying the flickering effects

Gandam A, Sidhu JS, Verma S, Jhanjhi NZ, Nayyar A, Abouhawwash M, et al.

PLoS One, 2021;16(5):e0250959.
PMID: 33970949 DOI: 10.1371/journal.pone.0250959

Compression at a very low bit rate(≤0.5bpp) causes degradation in video frames with standard decoding algorithms like H.261, H.262, H.264, and MPEG-1 and MPEG-4, which itself produces lots of artifacts. This paper focuses on an efficient pre-and post-processing technique (PP-AFT) to address and rectify the problems of quantization error, ringing, blocking artifact, and flickering effect, which significantly degrade the visual quality of video frames. The PP-AFT method differentiates the blocked images or frames using activity function into different regions and developed adaptive filters as per the classified region. The designed process also introduces an adaptive flicker extraction and removal method and a 2-D filter to remove ringing effects in edge regions. The PP-AFT technique is implemented on various videos, and results are compared with different existing techniques using performance metrics like PSNR-B, MSSIM, and GBIM. Simulation results show significant improvement in the subjective quality of different video frames. The proposed method outperforms state-of-the-art de-blocking methods in terms of PSNR-B with average value lying between (0.7-1.9db) while (35.83-47.7%) reduced average GBIM keeping MSSIM values very close to the original sequence statistically 0.978.

Matched MeSH terms: Image Enhancement/methods*
Fulltext Realistic real-time outdoor rendering in augmented reality

Kolivand H, Sunar MS

PLoS One, 2014;9(9):e108334.
PMID: 25268480 DOI: 10.1371/journal.pone.0108334

Realistic rendering techniques of outdoor Augmented Reality (AR) has been an attractive topic since the last two decades considering the sizeable amount of publications in computer graphics. Realistic virtual objects in outdoor rendering AR systems require sophisticated effects such as: shadows, daylight and interactions between sky colours and virtual as well as real objects. A few realistic rendering techniques have been designed to overcome this obstacle, most of which are related to non real-time rendering. However, the problem still remains, especially in outdoor rendering. This paper proposed a much newer, unique technique to achieve realistic real-time outdoor rendering, while taking into account the interaction between sky colours and objects in AR systems with respect to shadows in any specific location, date and time. This approach involves three main phases, which cover different outdoor AR rendering requirements. Firstly, sky colour was generated with respect to the position of the sun. Second step involves the shadow generation algorithm, Z-Partitioning: Gaussian and Fog Shadow Maps (Z-GaF Shadow Maps). Lastly, a technique to integrate sky colours and shadows through its effects on virtual objects in the AR system, is introduced. The experimental results reveal that the proposed technique has significantly improved the realism of real-time outdoor AR rendering, thus solving the problem of realistic AR systems.

Matched MeSH terms: Image Enhancement/methods*
Fulltext Medical image visual appearance improvement using bihistogram Bezier curve contrast enhancement: data from the Osteoarthritis Initiative

Gan HS, Swee TT, Abdul Karim AH, Sayuti KA, Abdul Kadir MR, Tham WK, et al.

ScientificWorldJournal, 2014;2014:294104.
PMID: 24977191 DOI: 10.1155/2014/294104

Well-defined image can assist user to identify region of interest during segmentation. However, complex medical image is usually characterized by poor tissue contrast and low background luminance. The contrast improvement can lift image visual quality, but the fundamental contrast enhancement methods often overlook the sudden jump problem. In this work, the proposed bihistogram Bezier curve contrast enhancement introduces the concept of "adequate contrast enhancement" to overcome sudden jump problem in knee magnetic resonance image. Since every image produces its own intensity distribution, the adequate contrast enhancement checks on the image's maximum intensity distortion and uses intensity discrepancy reduction to generate Bezier transform curve. The proposed method improves tissue contrast and preserves pertinent knee features without compromising natural image appearance. Besides, statistical results from Fisher's Least Significant Difference test and the Duncan test have consistently indicated that the proposed method outperforms fundamental contrast enhancement methods to exalt image visual quality. As the study is limited to relatively small image database, future works will include a larger dataset with osteoarthritic images to assess the clinical effectiveness of the proposed method to facilitate the image inspection.

Matched MeSH terms: Image Enhancement/methods*
Fulltext Completed local ternary pattern for rotation invariant texture classification

Rassem TH, Khoo BE

ScientificWorldJournal, 2014;2014:373254.
PMID: 24977193 DOI: 10.1155/2014/373254

Despite the fact that the two texture descriptors, the completed modeling of Local Binary Pattern (CLBP) and the Completed Local Binary Count (CLBC), have achieved a remarkable accuracy for invariant rotation texture classification, they inherit some Local Binary Pattern (LBP) drawbacks. The LBP is sensitive to noise, and different patterns of LBP may be classified into the same class that reduces its discriminating property. Although, the Local Ternary Pattern (LTP) is proposed to be more robust to noise than LBP, however, the latter's weakness may appear with the LTP as well as with LBP. In this paper, a novel completed modeling of the Local Ternary Pattern (LTP) operator is proposed to overcome both LBP drawbacks, and an associated completed Local Ternary Pattern (CLTP) scheme is developed for rotation invariant texture classification. The experimental results using four different texture databases show that the proposed CLTP achieved an impressive classification accuracy as compared to the CLBP and CLBC descriptors.

Matched MeSH terms: Image Enhancement/methods*

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