Image/video quality assessment

Author: Yuchieh Lin, Tsung-Jung Liu, Weisi Lin, and C.-C. Jay Kuo

This is a joint work during my internship in Mediatek in summer 2013.

Peak signal-to-noise ratio (PSNR) has been widely used to assess the quality of distorted images or videos with respect to their original ones for a long history. Human visual experience is affected by several psycho-visual factors, but PSNR does not take these factors into account. Thus, image and video quality metrics (IQM and VQM) [1] are proposed to emulate perceptional visual quality.

For image quality assessment, we developed a framework [2] to integrate visual saliency model to existing IQMs, such as SSIM and FSIM. For video quality assessment, we are working on building a new video database. Through this database, we would develop an algorithm for video quality assessment

So far, image or video quality metrics are not extensively applied to practical usage. One important reason is that the performance and complexity of no-reference algorithms are still not satisfied. We want to develop and employ no-reference IQM and VQM to enhance existing applications. We are facing a trade-off between performance and complexity.

• [1] Tsung-Jung Liu, Yu-Chieh Lin, Weisi Lin and C.-C. Jay Kuo, “Visual quality assessment: recent developments, coding applications and future trends,” APSIPA Transactions on Signal and Information Processing, 2013
• [2] Joe Yuchieh Lin, Tsung Jung Liu, Weisi Lin and C.-C. Jay Kuo, “Visual-saliencyenhanced image quality assessment indices,” APSIPA Annual Summit and Conference, Kao-Hsiung, Taiwan, Oct. 29-Nov. 1, 2013.