High-resolution image reconstruction using joint constrained edge pattern recognition and POCS formulation

The super-resolution image reconstruction techniques have been proven to be extremely useful in early vision, video surveillance, and other applications. However, the artifacts presented in the reconstructed images are very annoying. This paper presents a hybrid super-resolution image reconstruction algorithm which utilizes joint constrained edge pattern recognition and POCS formulation. A novel framework for the recognition of the constrained edge pattern of low-resolution pixels has been developed. Experimental results are also provided to demonstrate the effectiveness of the proposed technique.