Paper Info
Title
Exact Histogram Specification Optimized for Structural Similarity
Abstract
An exact global histogram specification (EGHS) method modifies its input image to have a specified global histogram. Applications of EGHS include image (contrast) enhancement (e.g., by histogram equalization) and histogram watermarking. Performing EGHS on an image, however, may reduce its visual quality. Starting from the output of a generic EGHS method, we maximize the structural similarity index (SSIM) between the original image (before EGHS) and the EGHS result iteratively. Essential in this process is the computationally simple and accurate formula we derive for SSIM gradient. As it is based on gradient ascent, the proposed EGHS always converges. Experimental results confirm that while obtaining the histogram exactly as specified, the proposed method invariably outperforms the existing methods in terms of visual quality of the result. The computational complexity of the proposed method is shown to be of the same order as that of the existing methods.
Year
DOI
Venue
2009
10.1007/s10043-009-0119-z
OPTICAL REVIEW
Keywords
Field
DocType
histogram modification,histogram equalization,optimization for perceptual visual quality,structural similarity gradient ascent,histogram watermarking,contrast enhancement
Computer vision,Histogram,Gradient descent,Digital watermarking,Histogram matching,Adaptive histogram equalization,Artificial intelligence,Balanced histogram thresholding,Histogram equalization,Physics,Computational complexity theory
Journal
Volume
Issue
ISSN
16
6
1340-6000
Citations 
PageRank 
References 
13
0.81
16
Authors
1
Name
Order
Citations
PageRank
Alireza Nasiri Avanaki1488.82