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Combinational image enhancement method based on wavelet domain

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Category: Information technologies, systems analysis and administration

Last Updated on 08 February 2016

Published on 08 February 2016

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Authors:

Defa Hu, Hunan University of Commerce, Changsha, Hunan, China

Zhuang Wu, Capital University of Economics and Business, Beijing, China

Abstract:

Purpose. The image enhancement technique is to highlight the interesting features or suppress the unnecessary features of the image, and it is a basic image processing technique. The article presents a series of study about how to enhance degra-ded image and get desirable effect. The combinational image enhancement measures based on wavelet domain have been developed, which are very helpful for image enhancement, improve the degraded image contrast greatly, and effectively enhance the overall image quality.

Methodology. The high-frequency and low-frequency components in the original image were separated by wavelet decomposition. Different methods were employed to enhance the image detail components of different frequency scopes and highlight the details of different scales. The low-frequency and high-frequency components were combined through the wavelet reconstruction to obtain the final enhanced image so as to improve the visual effect of the image.

Findings. A new wavelet domain algorithm was proposed for image enhancement. It adjusts the lightness of the image, expands the dynamic grayscale scope of the image, and enhances the contrast. The method carries out the self-adaptive enhancement of an image by some appropriate correction in the degraded image clarity.

Originality. The image enhancement method based on wavelet domain has been analysed sistematically. The traditional wavelet analysis method was improved according to the different collected information loss level of the degraded image.

Practical value. The research results greatly enhance the details of the image, improve the overall clarity; and the best effect is achieved when the algorithm is used to improve degraded images. The algorithm can improve the degraded image contrast greatly, effectively enhance the overall image quality without losing the image information during the processing. 

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