Super-resolution reconstruction of image sequences compressed with DWT-based techniques

Spatial domain based super-resolution reconstruction techniques, which were designed for uncompressed video to produce high-resolution image or image sequences, may not work well when applied directly to compressed videos, especially to those with severe quantization errors. Here a reconstruction approach designed for videos or image sequences, which were compressed using DWT-based techniques, is presented. This method utilizes the theory of projection onto convex sets (POCS) with a new projection operator based on Discrete Wavelet Transformation (DWT) for reducing blurring artifacts. It also applies maximum a posteriori (MAP) estimation techniques to remove ringing noises from restored images. Experimental results show that such approach could effectively recover objects ' edges and details that were blurred during compressing process while, expanding image 's size simultaneously.