Abstract
A novel adaptive resolution upconversion algorithm that is robust to compression artifacts is proposed. This method is based on classification of local image patterns using both structure information and activity measure to explicitly distinguish pixels into content or coding artifacts. The structure information is represented by adaptive dynamic-range coding and the activity measure is the combination of local entropy and dynamic range. For each pattern class, the weighting coefficients of upscaling are optimized by a least-mean-square (LMS) training technique, which trains on the combination of the original images and the compressed downsampled versions of the original images. Experimental results show that our proposed upconversion approach outperforms other classification-based upconversion and artifact reduction techniques in concatenation.
Highlights
With the continuous demand of higher picture quality, the resolution of high-end TV products is rapidly increasing
A pixel and its surrounding region can be classified based on the structure, which is represented by Adaptive dynamic-range coding (ADRC), and the activity measure, which is the local entropy plus dynamic range
All the pixels and their neighborhoods belonging to a specific class and their corresponding pixels in the reference images are accumulated, and the optimal coefficients are obtained by making the mean square error (MSE) minimized statistically
Summary
With the continuous demand of higher picture quality, the resolution of high-end TV products is rapidly increasing. The resolution of broadcasting programs or video on storage discs is usually lower than that of high-definition (HD) TV. Due to the bandwidth limit of the broadcasting channels and the capacity limit of the storage media, the video materials are always compressed with various compression standards, such as MPEG1/2/4 and H.26x These block-transform-based codecs divide the image or video frame into nonoverlapping blocks (usually with the size of 8 × 8 pixels), and apply discrete cosine transform (DCT) on them. The coding artifacts will be preserved after upscaling. We propose to remove coding artifacts and apply resolution upconversion simultaneously in this paper. We propose a single-frame processing solution for resolution upconversion of compressed images and video.
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