A high-resolution image reconstuction method from low-resolution image sequence

This paper presents a high-resolution image reconstruction method from low-resolution image sequence. It is difficult to recognize details from a low-resolution image because of severe aliasing and poor image quality, hence recognition from the low-resolution image may result in false recognition decision. In order to improve the recognition performance, the proposed method performs a reconstruction-based super-resolution technique as a preprocessing. Then, we adopt a learning-based super-resolution technique to make high-resolution images. The proposed method also considers the illumination change between an input image and training images. To verify the accuracy and reliability of the proposed method, experiments and numerical analyses were performed with several video sequences of a moving car that simulate real surveillance systems.