Adaptive Image De-noising Method Based on Spatial Autocorrelation

An adaptive image de-noising method based on spatial autocorrelation is proposed to effectively remove image noise and preserve structural information. A residual image is obtained using average filtering and then subtracted from the original image. The high-pass residual image should be a combination of boundary and noise. The autocorrelation of each pixel is calculated on the residual image, and then the image is adaptively filtered based on the autocorrelation values. The results show that Lena adaptive filtering quality is significantly better than global image filtering. This method was also applied to a simulated Huffman phantom PET image for validation and the same results were obtained. The spatial autocorrelation is calculated on the high-pass residual image and then adaptive de-noising is performed. The proposed method will be further developed and applied to image de-noising and image quality improvement.