Abstract
In the process of denoising color images, it is very important to enhance the edge and texture information of the images. Image quality can usually be improved by eliminating noise and enhancing contrast. Based on the adaptive wavelet threshold shrinkage algorithm and considering structural characteristics on the basis of color image denoising, this paper describes a method that further enhances the edge and texture details of the image using guided filtering. The use of guided filtering allows edge details that cannot be discriminated in grayscale images to be preserved. The noisy image is decomposed into low-frequency and high-frequency subbands using discrete wavelets, and the contraction function of threshold shrinkage is selected according to the energy in the vicinity of the wavelet coefficients. Finally, the edge and texture information of the denoised color image are enhanced by guided filtering. When the guiding image is the original noiseless image itself, the guided filter can be used as a smoothing operator for preserving edges, resulting in a better effect than bilateral filtering. The proposed method is compared with the adaptive wavelet threshold shrinkage denoising algorithm and the bilateral filtering algorithm. Experimental results show that the proposed method achieves superior color image denoising compared to these conventional techniques.
Highlights
During their acquisition and transmission, images are adversely affected by noise
The denoising of color images often results in the loss of some edge and texture information, making the image blurred and creating a poor visual effect
This paper presents a new color image denoising method based on the adaptive wavelet threshold shrinkage algorithm combined with image structure-based guided filtering [15]
Summary
During their acquisition and transmission, images are adversely affected by noise. Color images contain better visual effects than gray image in terms of visual perception, and the edge information of color images is more abundant than in gray images. The reason is that classic algorithms could suppress the Gaussian noise effectively, but, at the same time, these methods fail to maintain the quality of denoised color images (like, texture) and may blur edges in the image. To address these short comings, this paper proposes a method based on image structure using adaptive wavelet threshold and guided filter to maintain edges when denoising. The details in color image, like texture, are more abundant and saturation is more greater On this basis, this paper presents a new color image denoising method based on the adaptive wavelet threshold shrinkage algorithm combined with image structure-based guided filtering [15].
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