Image resizing is to change an image size by upsampling or downsampling of a digital image. Most still images and video frames are given in a compressed domain on digital media. Image resizing of a compressed image can be performed in a spatial domain via decompression and recompression. In general, resizing of a compressed image in a compressed domain is much faster than that in a spatial domain. In this paper, we propose a novel approach to resize images with L/M resizing ratio in the discrete cosine transform (DCT) domain, which exploits the multiplication-convolution property of DCT (the multiplication in spatial domain corresponds to the symmetric convolution in DCT domain). When an image is given in terms of its block-DCT coefficients, its resized image is also obtained in block-DCT coefficients. The proposed approach is computationally fast and produces visually fine images with high PSNR.