Image contrast enhancement based on intensity expansion-compression

Contrast enhancement for digital color image using a new approach.Identified cause of information content loss in conventional histogram equalization.Cause of generation of viewing artefacts identified.Intensity range fully utilized to carry scene information by expansion-compression.Preservation of features in the original image. In most image based applications, input images of high information content are required to ensure that satisfactory performances can be obtained from subsequent processes. Manipulating the intensity distribution is one of the popular methods that have been widely employed. However, this conventional procedure often generates undesirable artifacts and causes reductions in the information content. An approach based on expanding and compressing the intensity dynamic range is here proposed. By expanding the intensity according to the polarity of local edges, an intermediate image of continuous intensity spectrum is obtained. Then, by compressing this image to the allowed intensity dynamic range, an increase in information content is ensured. The combination of edge guided expansion with compression also enables the preservation of fine details contained in the input image. Experimental results show that the proposed method outperforms other approaches, which are based on histogram divisions and clippings, in terms of image contrast enhancement.

[1]  Turgay Çelik,et al.  Spatial Mutual Information and PageRank-Based Contrast Enhancement and Quality-Aware Relative Contrast Measure , 2016, IEEE Transactions on Image Processing.

[2]  Rae-Hong Park,et al.  Histogram-Based Locality-Preserving Contrast Enhancement , 2015, IEEE Signal Processing Letters.

[3]  Abd. Rahman Ramli,et al.  Contrast enhancement using recursive mean-separate histogram equalization for scalable brightness preservation , 2003, IEEE Trans. Consumer Electron..

[4]  Qiang Li,et al.  Automatic road damage detection using high-resolution satellite images and road maps , 2013, 2013 IEEE International Geoscience and Remote Sensing Symposium - IGARSS.

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

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

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

[8]  Weiming Zhang,et al.  Reversible data hiding in medical images with enhanced contrast in texture area , 2016, Digit. Signal Process..

[9]  Yu Li,et al.  Mahalanobis distance based on fuzzy clustering algorithm for image segmentation , 2015, Digit. Signal Process..

[10]  Ngaiming Kwok,et al.  Image contrast enhancement with brightness preservation using an optimal gamma correction and weighted sum approach , 2015 .

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

[12]  Jun Wang,et al.  An advanced gradient histogram and its application for contrast and gradient enhancement , 2015, J. Vis. Commun. Image Represent..

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

[14]  Ngaiming Kwok,et al.  Intensity and edge based adaptive unsharp masking filter for color image enhancement , 2016 .

[15]  Ramazan Duvar,et al.  Fuzzy fusion based high dynamic range imaging using adaptive histogram separation , 2015, IEEE Transactions on Consumer Electronics.

[16]  Yanling Xu,et al.  Computer vision technology for seam tracking in robotic GTAW and GMAW , 2015 .

[17]  S. C. F. Lin,et al.  Dark channel prior based image de-hazing: A review , 2015, 2015 5th International Conference on Information Science and Technology (ICIST).

[18]  Y. Y. Tan,et al.  Recursive sub-image histogram equalization applied to gray scale images , 2007, Pattern Recognit. Lett..

[19]  Jiankun Hu,et al.  Superpixel-Based Graphical Model for Remote Sensing Image Mapping , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[20]  Yücel Altunbasak,et al.  A Histogram Modification Framework and Its Application for Image Contrast Enhancement , 2009, IEEE Transactions on Image Processing.

[21]  Shanq-Jang Ruan,et al.  Improved local histogram equalization with gradient-based weighting process for edge preservation , 2015, Multimedia Tools and Applications.

[22]  Yan Liang,et al.  Adaptive extended piecewise histogram equalisation for dark image enhancement , 2015, IET Image Process..

[23]  Zhou Wang,et al.  A Patch-Structure Representation Method for Quality Assessment of Contrast Changed Images , 2015, IEEE Signal Processing Letters.

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