Brightness and contrast controllable image enhancement based on histogram specification

Abstract Histogram based image enhancement techniques are widely used for performing contrast enhancement in images. However, most histogram based image enhancement methods have insufficient capability to freely tune the brightness and contrast of enhanced image. In this paper, two novel histogram based image enhancement algorithms are proposed. The proposed algorithms provide the way to control the brightness and contrast of enhanced image by adjusting two parameters. The principles for parameter selection are also discussed in this paper. Experimental results demonstrate a better performance of the proposed methods in both perceptual quality and image quality assessment metrics than the existing histogram based methods.

[1]  Boualem Boashash,et al.  A distortion-free contrast enhancement technique based on a perceptual fusion scheme , 2017, Neurocomputing.

[2]  E. Peli.  Contrast in complex images. , 1990, Journal of the Optical Society of America. A, Optics and image science.

[3]  Lai Khin Wee,et al.  Multiobjectives bihistogram equalization for image contrast enhancement , 2014 .

[4]  Stuart Crozier,et al.  Edge intensity normalization as a bias field correction during balloon snake segmentation of breast MRI , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  Oleksiy B. Pogrebnyak,et al.  Efficiency of texture image enhancement by DCT-based filtering , 2016, Neurocomputing.

[6]  He Jianhua,et al.  Image fusion method based on average grads and wavelet contrast , 2012 .

[7]  Sos S. Agaian,et al.  Transform-based image enhancement algorithms with performance measure , 2001, IEEE Trans. Image Process..

[8]  Shanq-Jang Ruan,et al.  Dynamic contrast enhancement based on histogram specification , 2005, IEEE Transactions on Consumer Electronics.

[9]  MengChu Zhou,et al.  An Efficient Non-Negative Matrix-Factorization-Based Approach to Collaborative Filtering for Recommender Systems , 2014, IEEE Transactions on Industrial Informatics.

[10]  Raymond H. Chan,et al.  Journal of Mathematical Imaging and Vision 2012 1 Exact Histogram Specification for Digital Images Using a Variational Approach , 2022 .

[11]  Sos S. Agaian,et al.  Transform Coefficient Histogram-Based Image Enhancement Algorithms Using Contrast Entropy , 2007, IEEE Transactions on Image Processing.

[12]  Maheza Irna Mohamad Salim,et al.  Multiobjectives bihistogram equalization for image contrast enhancement , 2014, Complex..

[13]  Ying Li,et al.  Automatic SAR image enhancement based on nonsubsampled contourlet transform and memetic algorithm , 2014, Neurocomputing.

[14]  Om Prakash Verma,et al.  Fuzzy-Contextual Contrast Enhancement , 2017, IEEE Transactions on Image Processing.

[15]  Hui Zhu,et al.  Image Contrast Enhancement by Constrained Local Histogram Equalization , 1999, Comput. Vis. Image Underst..

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

[17]  John C. Russ,et al.  Image Enhancement in the Spatial Domain , 2015 .

[18]  Hong Zhang,et al.  Facial expression recognition via learning deep sparse autoencoders , 2018, Neurocomputing.

[19]  Yang Gao,et al.  Local histogram specification for face recognition under varying lighting conditions , 2014, Image Vis. Comput..

[20]  Turgay Çelik,et al.  Two-dimensional histogram equalization and contrast enhancement , 2012, Pattern Recognit..

[21]  Yang Gao,et al.  Fast Local Histogram Specification , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[22]  Chul Lee,et al.  Contrast Enhancement Based on Layered Difference Representation of 2D Histograms , 2013, IEEE Transactions on Image Processing.

[23]  Lee-Sup Kim,et al.  An advanced contrast enhancement using partially overlapped sub-block histogram equalization , 2001, IEEE Trans. Circuits Syst. Video Technol..

[24]  Frédo Durand,et al.  Fast Local Laplacian Filters , 2014, ACM Trans. Graph..

[25]  MengChu Zhou,et al.  A Nonnegative Latent Factor Model for Large-Scale Sparse Matrices in Recommender Systems via Alternating Direction Method , 2016, IEEE Transactions on Neural Networks and Learning Systems.

[26]  Hong Zhang,et al.  Denoising and deblurring gold immunochromatographic strip images via gradient projection algorithms , 2017, Neurocomputing.

[27]  Turgay Çelik,et al.  Spatial Entropy-Based Global and Local Image Contrast Enhancement , 2014, IEEE Transactions on Image Processing.

[28]  Joonki Paik,et al.  Contrast enhancement system using spatially adaptive histogram equalization with temporal filtering , 1998 .

[29]  Seung-Won Jung.  Two-dimensional histogram specification using two-dimensional cumulative distribution function , 2014 .

[30]  David Menotti,et al.  Multi-Histogram Equalization Methods for Contrast Enhancement and Brightness Preserving , 2007, IEEE Transactions on Consumer Electronics.

[31]  Dinu Coltuc,et al.  Exact histogram specification , 2006, IEEE Transactions on Image Processing.

[32]  Hao-quan Wang,et al.  Multi-Mode Medical Image Fusion Algorithm Based on Principal Component Analysis , 2009, 2009 International Symposium on Computer Network and Multimedia Technology.

[33]  Yi-Ping Hung,et al.  Illumination Compensation Using Oriented Local Histogram Equalization and its Application to Face Recognition , 2012, IEEE Transactions on Image Processing.

[34]  MengChu Zhou,et al.  Incorporation of Efficient Second-Order Solvers Into Latent Factor Models for Accurate Prediction of Missing QoS Data , 2018, IEEE Transactions on Cybernetics.

[35]  Shuai Li,et al.  Symmetric and Nonnegative Latent Factor Models for Undirected, High-Dimensional, and Sparse Networks in Industrial Applications , 2017, IEEE Transactions on Industrial Informatics.

[36]  Fuad E. Alsaadi,et al.  Deep Belief Networks for Quantitative Analysis of a Gold Immunochromatographic Strip , 2016, Cognitive Computation.

[37]  Craig K. Abbey,et al.  Fast algorithms for histogram matching: Application to texture synthesis , 2000, J. Electronic Imaging.

[38]  Sankar K. Pal,et al.  Automatic Exact Histogram Specification for Contrast Enhancement and Visual System Based Quantitative Evaluation , 2011, IEEE Transactions on Image Processing.

[39]  Chul Lee,et al.  Power-Constrained Contrast Enhancement for Emissive Displays Based on Histogram Equalization , 2012, IEEE Transactions on Image Processing.

[40]  Karim Faez,et al.  Visual object tracking with online weighted chaotic multiple instance learning , 2017, Neurocomputing.

[41]  Chris H. Q. Ding,et al.  Convex and Semi-Nonnegative Matrix Factorizations , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

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