A reduced-reference perceptual image and video quality metric based on edge preservation (original) (raw)
2012, EURASIP Journal on Advances in Signal Processing
Related papers
Image quality assessment based on edge preservation
Signal Processing Image Communication, 2012
Objective image/video quality metrics which accurately represent the subjective quality of processed images are of paramount importance for the design and assessment of an image compression and transmission system. In some scenarios, it is also important to evaluate the quality of the received image with minimal reference to the transmitted one. For instance, for closed-loop optimization of a transmission system, the image quality measure can be evaluated at the receiver and provided as feedback information to the system controller. The original image-prior to compression and transmissionis not usually available at the receiver side, and it is important to rely at the receiver side on an objective quality metric that does not need reference or needs minimal reference to the original image. The observation that the human eye is very sensitive to edge and contour information of an image underpins the proposal of our reduced reference (RR) quality metric, which compares edge information between the distorted and the original image. Results highlight that the metric correlates well with subjective observations, also in comparison with commonly used full-reference metrics and with a state-of-the-art reduced reference metric.
Proceedings of SPIE, 2003
One of the most active research area in the watermarking community is the research in dealing with geometric distortion. The geometric distortion problem has two aspects, namely its effect on watermark detectability and its effect on the perceptual quality of the watermarked data. Most research in this area has been concentrated on addressing the first aspect of the problem, and research on objective visual quality assessment of geometrically distorted images is not widely discussed in the literature. As a consequence, there is a lack of objective visual quality measurement for this class of distortion. In this paper we propose a method of objectively assessing the perceptual quality of geometrically distorted images. Our approach is based on the modeling of a complex, global geometric distortion using local, simpler geometric transformation models. The locality of this simpler geometric transformation determines the visual quality of the distorted images.
Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.