Adaptive histogram equalization and its variations
Computer Vision, Graphics, and Image Processing
Fundamentals of digital image processing
Fundamentals of digital image processing
Contrast enhancement technique based on local detection of edges
Computer Vision, Graphics, and Image Processing
Automatic, adaptive, brightness independent contrast enhancement
Signal Processing
Introduction to the theory of neural computation
Introduction to the theory of neural computation
An alternative algorithm for adaptive histogram equalization
Graphical Models and Image Processing
Practical algorithms for image analysis: description, examples, and code
Practical algorithms for image analysis: description, examples, and code
Introductory Digital Image Processing: A Remote Sensing Perspective
Introductory Digital Image Processing: A Remote Sensing Perspective
Digital Picture Processing
Image Analysis and Mathematical Morphology
Image Analysis and Mathematical Morphology
Adaptive image contrast enhancement using generalizations of histogram equalization
IEEE Transactions on Image Processing
Gray and color image contrast enhancement by the curvelet transform
IEEE Transactions on Image Processing
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In this paper an algorithm for optical quality enhancement in low contrast images is proposed. The brightness dynamic region is increased using a non-linear transformation function, which is adapted from the local contrast. In a new approach, the local contrast is defined in every central pixel, using a four direction masking method and a statistical estimation of the local contrast value. Two adaptive thresholds locate the exact pixel positions where the proposed contrast adjustment algorithm is used to improve the image quality. In the evaluation process, several artificially distorted images are enhanced and the mean square error and peak noise ratio between the restored and the original images are estimated. The experimental results show both objective and subjective improvements in the image quality.