Abstract: In order to solve the problems of fuzzy patterns and edge distortion of Mongolian traditional furniture, this paper proposes an image enhancement method based on weighted transformation. Firstly, Mongolian furniture patterns are decomposed into RGB components, and lifting wavelet transform, stationary wavelet transform, interpolation algorithm and inverse lifting wavelet transform are adopted to obtain the high- resolution patterns. Finally, the weighted transformation function is used to modify the histogram, and the histogram with the smallest contribution is filtered to obtain the high- resolution and contrast-enhanced patterns. This method is compared with the traditional histogram equalization and bicubic interpolation method. The experimental results show that the proposed method has better PSNR (Peak Signal to Noise Ratio) and SSIM (Structure Similarity Index) than the tradi-tional histogram equalization and bicubic interpolation methods, and can effectively enhance Mongolian furniture patterns. The proposed method  is of great value to the repair and protection of traditional Mongolian furniture patterns.

Key words: Mongolian furniture pattern, wavelet transform, interpolation algorithm, weighted transform, image enhancement