关键词: 图像放大, 小波插值, 自蛇模型, 双线性插值

Abstract: In view of blurred and jagged edges in the image magnified by traditional interpolation, combining with multi-resolution analysis and time-frequency localization characterized by wavelet, a sharpening method based on wavelet-interpolation and improved self-snake model is proposed. This method zooms in the image with the combination of wavelet- interpolation algorithm and uses improved self-snake model to correct the edge for magnified image, while in terms of noise image, an improved self-snake model is used to sharpen the image, and then enlarge the processed image by wavelet-interpolation. Experimental results show that this method has a more accurate sharpness of the edge profiles and a higher recognition of the detail section compared with the traditional sharpening algorithms in enlarged images, at the same time, it can effectively improve the PSNR of the enlarged image.

Key words: image zooming, wavelet-interpolation, self-snake model, bilinear interpolation