Image enhancement method based on wavelet and adaptive fractional differential

To acquire images with abundant detail features and obvious differences among weak details, an improved image enhancement method based on wavelet and adaptive fractional differential is proposed in this paper. According to differential box-counting method, the fractal dimension and the differential order can be obtained. Afterwards the fractional filter templates of removing the horizontal direction, removing the vertical direction and removing the diagonal direction are designed. For the sake of extracting more image edge information, the wavelet coefficients of time-frequency decomposition are processed by the corresponding templates, and the processed wavelet coefficients will be reconstructed and linearly superimposed to obtain the enhanced images and the edge images. The experimental results show that this improved method can preserve the low-frequency information of the image non-linearly. The ability to enhance and extract the high-frequency edge information is superior to that of Tiansi algorithm and other improved algorithms referred in this paper. The method can also determine the ideal differential order adaptively, thereby achieving the optimal enhancement effects.