Skip to Main Content
The paper proposes a pixel-based post-processing algorithm to enhance the quality of motion JPEG (MJPEG) by exploiting the temporal redundancies of the decoded frames. The technique permits reconstruction of the high frequency coefficients lost during quantization, thereby reducing ringing artifacts. Based on the linearization of the quantization function, the error between the estimated and original coefficients is analyzed for both cases of ideal and real video sequences. Blocking artifact reduction is verified by a reduction in the variance of this coefficient error. The condition of valid motion vectors to get quality improvement is considered based on these errors. The algorithm is also extended to find the optimal filter for a general estimation scheme based on an arbitrary number of frames. Results in visual and peak signal-to-noise ratio improvement using both integer and subpixel motion vectors are verified by simulations on video sequences.