Image Filtering in the Compressed Domain

Abstract

Linear filtering of images is usually performed in the spatial domain using the linear convolution operation. In the case of images stored in the block DCT space, the linear filtering is usually performed on the sub-image obtained by applying an inverse DCT to the block DCT data. However, this results in severe blocking artifacts caused by the boundary conditions of individual blocks as pixel values outside the boundaries of the blocks are assumed to be zeros. To get around this problem, we propose to use the symmetric convolution operation in such a way that the operation becomes equivalent to the linear convolution operation in the spatial domain. This is achieved by operating on larger block sizes in the transform domain. We demonstrate its applications in image sharpening and removal of blocking artifacts directly in the compressed domain.