Fundamentals of digital image processing
Fundamentals of digital image processing
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
An Image Enhancement Method Based on Gamma Correction
ISCID '09 Proceedings of the 2009 Second International Symposium on Computational Intelligence and Design - Volume 01
Color image enhancement using retinex with robust envelope
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Color Image Enhancement Using Multiscale Retinex with Modified Color Restoration Technique
EAIT '11 Proceedings of the 2011 Second International Conference on Emerging Applications of Information Technology
Short Communication: Histogram Modified Local Contrast Enhancement for mammogram images
Applied Soft Computing
A multiscale retinex for bridging the gap between color images and the human observation of scenes
IEEE Transactions on Image Processing
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In this paper, a Particle Swarm Optimization (PSO) method for tuning the parameters of multiscale retinex based color image enhancement is presented. The image enhancement using multiscale retinex scheme heavily depends on parameters such as Gaussian surround space constants, number of scales, gain and offset etc. Due to hard selection of these parameters, PSO has been used in order to investigate the optimal parameters for the best image enhancement. The PSO method of parameter tuning adopted for multiscale retinex with modified color restoration (MSRMCR) algorithm achieves very good quality of reconstructed images, far better than that possible with the other existing methods. The presented algorithm is compared with other promising enhancement schemes such as histogram equalization, NASA's multiscale retinex with color restoration (MSRCR), Improved MSRCR (IMSRCR), and Photoflair software. The quality of the enhanced image is validated iteratively using an efficient objective criterion which is based on entropy and edge information of an image. Finally, the quality of the reconstructed images obtained by the proposed method is evaluated using Wavelet Energy (WE) metric. The experimental results presented shows that color image enhanced by the proposed algorithm are clearer, vivid and efficient.