Denoising algorithm for unbalanced noise fuzzy intelligent image

Abstract

This paper presents an intelligent noise reduction algorithm for unbalanced noise fuzzy image. Firstly, a segmentation algorithm based on inter class variance maximization is adopted, and the image is divided into two types of background and target, to determine the threshold value; then, according to the change of the local, noise is adaptively reduced, so as to achieve the purpose of intelligent noise reduction. Experimental results show that the denoising effect of the proposed algorithm is better than that of other algorithms. The edge details are preserved and the visual effect is enhanced.

Subject Classification:

• MSC2010
• 94A99

Keywords:

• Unbalanced noise
• Fuzzy image
• Intelligent noise reduction
• Fuzzy function
• Wavelet coefficient