Subjective evaluation of spatial resolution and quantization noise tradeoffs

Authors:
Soo Hyun Bae;Thrasyvoulos N. Pappas;Biing-Hwang Juang
Affiliations:
Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA;Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL;Center for Signal and Image Processing, Georgia Institute of Technology, Atlanta, GA
Venue:
IEEE Transactions on Image Processing
Year:
2009

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Abstract

Most full-reference fidelity/quality metrics compare the original image to a distorted image at the same resolution assuming a fixed viewing condition. However, in many applications, such as video streaming, due to the diversity of channel capacities and display devices, the viewing distance and the spatiotemporal resolution of the displayed signal may be adapted in order to optimize the perceived signal quality. For example, at low bitrate coding applications an observer may prefer to reduce the resolution or increase the viewing distance to reduce the visibility of the compression artifacts. The tradeoff between resolution/viewing conditions and visibility of compression artifacts requires new approaches for the evaluation of image quality that account for both image distortions and image size. In order to better understand such tradeoffs, we conducted subjective tests using two representative still image coders, JPEG and JPEG 2000. Our results indicate that an observerwould indeed prefer a lower spatial resolution (at a fixed viewing distance) in order to reduce the visibility of the compression artifacts, but not all the way to the point where the artifacts are completely invisible. Moreover, the observer is willing to accept more artifacts as the image size decreases. The subjective test results we report can be used to select viewing conditions for coding applications. They also set the stage for the development of novel fidelity metrics. The focus of this paper is on still images, but it is expected that similar tradeoffs apply to video.