Gaussian probability bi‐histogram equalization for enhancement of the pathological features in medical images

In order to enhance the pathological features of medical images and aid the medical diagnosis, the image enhancement is a necessary process. This study presented the Gaussian probability model combining with bi‐histogram equalization to enhance the contrast of pathological features in medical images. There are five different bi‐histogram equalizations, namely, bi‐histogram equalization (BBHE), dualistic sub‐image histogram equalization (DSIHE), bi‐histogram equalization with a plateau limit (BHEPL), bi‐histogram equalization median plateau limit (BHEPL‐D), and bi‐histogram equalization with modified histogram bins (BHEMHB). The entropy, contrast, absolute mean brightness error (AMBE), and skewness difference are used to quantize the enhancement results. From the experimental result, it is observed that the entropy and contrast of the images can be effectively enhanced by using Gaussian probability bi‐histogram equalizations, and the Gaussian probability bi‐histogram equalization median plateau limit (GPBHEPL‐D) has the best enhanced result. The proposed GPBHEPL‐D method is effective in strengthening the pathological features in medical images, so as to increase the efficiency of doctors' diagnoses and computer‐aided detection.

[1]  Qian Chen,et al.  Image enhancement based on equal area dualistic sub-image histogram equalization method , 1999, IEEE Trans. Consumer Electron..

[2]  George K. Matsopoulos,et al.  Medical imaging correction: A comparative study of five contrast and brightness matching methods , 2012, Comput. Methods Programs Biomed..

[3]  Chun-Ming Chang,et al.  A simple histogram modification scheme for contrast enhancement , 2010, IEEE Transactions on Consumer Electronics.

[4]  Kok-Swee Sim,et al.  Contrast enhancement dynamic histogram equalization for medical image processing application , 2011, Int. J. Imaging Syst. Technol..

[5]  Tae Jung Kim,et al.  Clinical significance of a solitary ground-glass opacity (GGO) lesion of the lung detected by chest CT. , 2007, Lung cancer.

[6]  Nor Ashidi Mat Isa,et al.  Adaptive contrast enhancement methods with brightness preserving , 2010, IEEE Transactions on Consumer Electronics.

[7]  V. Magudeeswaran,et al.  Brightness preserving bi‐level fuzzy histogram equalization for MRI brain image contrast enhancement , 2017, Int. J. Imaging Syst. Technol..

[8]  Xingming Sun,et al.  Reversible data hiding with contrast enhancement and tamper localization for medical images , 2017, Inf. Sci..

[9]  Ho Chul Kang,et al.  Low-dose 2D X-ray angiography enhancement using 2-axis PCA for the preservation of blood-vessel region and noise minimization , 2016, Comput. Methods Programs Biomed..

[10]  Abd. Rahman Ramli,et al.  Minimum mean brightness error bi-histogram equalization in contrast enhancement , 2003, IEEE Trans. Consumer Electron..

[11]  Iza Sazanita Isa,et al.  Automatic contrast enhancement of brain MR images using Average Intensity Replacement based on Adaptive Histogram Equalization (AIR-AHE) , 2017 .

[12]  Rafael C. González,et al.  Digital image processing using MATLAB , 2006 .

[13]  Haidi Ibrahim,et al.  Bi-histogram equalization with a plateau limit for digital image enhancement , 2009, IEEE Transactions on Consumer Electronics.

[14]  Takashi Furuhata,et al.  Linear Phase Emphasis Networks with Gaussian Function , 1987, IEEE Transactions on Broadcasting.

[15]  Kuldeep Singh,et al.  Image enhancement using Exposure based Sub Image Histogram Equalization , 2014, Pattern Recognit. Lett..

[16]  Juan Manuel Górriz,et al.  Skewness as feature for the diagnosis of Alzheimer's disease using SPECT images , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[17]  Kok-Swee Sim,et al.  Contrast enhancement of computed tomography images by adaptive histogram equalization‐application for improved ischemic stroke detection , 2012, Int. J. Imaging Syst. Technol..

[18]  P. Ganeshkumar,et al.  Computer aided brain tumor detection system using watershed segmentation techniques , 2015, Int. J. Imaging Syst. Technol..

[19]  V. Magudeeswaran,et al.  Contrast limited fuzzy adaptive histogram equalization for enhancement of brain images , 2017, Int. J. Imaging Syst. Technol..

[20]  Mark A. Haidekker,et al.  Enhanced dynamic range x-ray imaging , 2017, Comput. Biol. Medicine.

[21]  M. Ali Akber Dewan,et al.  A Dynamic Histogram Equalization for Image Contrast Enhancement , 2007, IEEE Transactions on Consumer Electronics.

[22]  Turgay Çelik,et al.  Automatic Image Equalization and Contrast Enhancement Using Gaussian Mixture Modeling , 2012, IEEE Transactions on Image Processing.

[23]  Nor Ashidi Mat Isa,et al.  Adaptive Image Enhancement based on Bi-Histogram Equalization with a clipping limit , 2014, Comput. Electr. Eng..

[24]  V. Rajamani,et al.  Contrast enhancement using real coded genetic algorithm based modified histogram equalization for gray scale images , 2015, Int. J. Imaging Syst. Technol..

[25]  Tinku Acharya,et al.  Image Processing: Principles and Applications , 2005, J. Electronic Imaging.

[26]  Amandeep Kaur,et al.  Contrast enhancement for cephalometric images using wavelet-based modified adaptive histogram equalization , 2017, Appl. Soft Comput..

[27]  Lixia Chen,et al.  An effective histogram modification scheme for image contrast enhancement , 2017, Signal Process. Image Commun..

[28]  S. Anand,et al.  Mammogram image enhancement by two-stage adaptive histogram equalization , 2015 .

[29]  Abdul Rahman Ramli,et al.  Review of brain MRI image segmentation methods , 2010, Artificial Intelligence Review.

[30]  Bo Li,et al.  Adaptive fractional differential approach and its application to medical image enhancement , 2015, Comput. Electr. Eng..

[31]  Yeong-Taeg Kim,et al.  Contrast enhancement using brightness preserving bi-histogram equalization , 1997 .

[32]  Ching-Hsue Cheng,et al.  Fast computation of Hessian-based enhancement filters for medical images , 2014, Comput. Methods Programs Biomed..

[33]  Nor Ashidi Mat Isa,et al.  Bi-histogram equalization using modified histogram bins , 2017, Appl. Soft Comput..

[34]  Samir Kumar Bandyopadhyay,et al.  Technique for preprocessing of digital mammogram , 2012, Comput. Methods Programs Biomed..

[35]  J. Anitha,et al.  Optimum wavelet based masking for the contrast enhancement of medical images using enhanced cuckoo search algorithm , 2016, Comput. Biol. Medicine.

[36]  Magudeeswaran Veluchamy,et al.  MRI brain image enhancement using brightness preserving adaptive fuzzy histogram equalization , 2018, Int. J. Imaging Syst. Technol..

[37]  Boris Escalante-Ramírez,et al.  Segmentation and optical flow estimation in cardiac CT sequences based on a spatiotemporal PDM with a correction scheme and the Hermite transform , 2016, Comput. Biol. Medicine.

[38]  P. Shanmugavadivu,et al.  Particle swarm optimized multi-objective histogram equalization for image enhancement , 2014 .

[39]  Bo Zhou,et al.  A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization , 2012 .

[40]  M L Mendelsohn,et al.  THE ANALYSIS OF CELL IMAGES * , 1966, Annals of the New York Academy of Sciences.

[41]  Huiqi Li,et al.  An enhancement method for color retinal images based on image formation model , 2017, Comput. Methods Programs Biomed..

[42]  Sanjay N. Talbar,et al.  Local gray level S-curve transformation - A generalized contrast enhancement technique for medical images , 2017, Comput. Biol. Medicine.

[43]  Ali Rehman,et al.  Recursive weighted multi-plateau histogram equalization for image enhancement , 2015 .