Image contrast enhancement during time-angular domain imaging through turbid media by estimation of background scattered light

2009 ◽  
Author(s):  
Eldon Ng ◽  
Fartash Vasefi ◽  
Bozena Kaminska ◽  
Glenn H. Chapman ◽  
Jeffrey J. L. Carson
Keyword(s):  
Contrast Enhancement ◽  
Scattered Light ◽  
Image Contrast ◽  
Turbid Media ◽  
Angular Domain ◽  
Image Contrast Enhancement ◽  
Imaging Through Turbid Media ◽  
Angular Domain Imaging

scholarly journals Image contrast enhancement in angular domain optical imaging of turbid media

2008 ◽  
Vol 16 (26) ◽  
pp. 21492 ◽  
Author(s):  
Fartash Vasefi ◽  
Bozena Kaminska ◽  
Glenn H. Chapman ◽  
Jeffrey J. Carson
Keyword(s):  
Optical Imaging ◽  
Contrast Enhancement ◽  
Image Contrast ◽  
Turbid Media ◽  
Angular Domain ◽  
Image Contrast Enhancement

DCT Coefficients Weighting (DCTCW)-Based Gray Wolf Optimization (GWO) for Brightness Preserving Image Contrast Enhancement

2021 ◽  
Author(s):  
Saorabh Kumar Mondal ◽  
Arpitam Chatterjee ◽  
Bipan Tudu
Keyword(s):  
Contrast Enhancement ◽  
Objective Evaluation ◽  
Brightness Distribution ◽  
Image Contrast ◽  
Optimization Techniques ◽  
Biological Behavior ◽  
Gray Wolf ◽  
Original Image ◽  
Image Characteristics ◽  
Image Contrast Enhancement

Image contrast enhancement (CE) is a frequent image enhancement requirement in diverse applications. Histogram equalization (HE), in its conventional and different further improved ways, is a popular technique to enhance the image contrast. The conventional as well as many of the later versions of HE algorithms often cause loss of original image characteristics particularly brightness distribution of original image that results artificial appearance and feature loss in the enhanced image. Discrete Cosine Transform (DCT) coefficient mapping is one of the recent methods to minimize such problems while enhancing the image contrast. Tuning of DCT parameters plays a crucial role towards avoiding the saturations of pixel values. Optimization can be a possible solution to address this problem and generate contrast enhanced image preserving the desired original image characteristics. Biological behavior-inspired optimization techniques have shown remarkable betterment over conventional optimization techniques in different complex engineering problems. Gray wolf optimization (GWO) is a comparatively new algorithm in this domain that has shown promising potential. The objective function has been formulated using different parameters to retain original image characteristics. The objective evaluation against CEF, PCQI, FSIM, BRISQUE and NIQE with test images from three standard databases, namely, SIPI, TID and CSIQ shows that the presented method can result in values up to 1.4, 1.4, 0.94, 19 and 4.18, respectively, for the stated metrics which are competitive to the reported conventional and improved techniques. This paper can be considered a first-time application of GWO towards DCT-based image CE.

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