In this paper we propose a fast adaptive image restoration filter using DCT-based block classification for reducing block artifacts in compressed images. In order to efficiently reduce block artifacts, edge direction of each block is classified by using the DCT coefficients, and the constrained least square (CLS) on the observation that the quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space-varying degradation operator. For real-time implementation, the proposed restoration filter can be realized in the form of a truncated FIR filter, which is suitable for postprocessing reconstructed images in HDTV, DVD, or video conference systems.