Subjective quality feedback by actual human viewers is crucial for reliable evaluation of various solutions and configurations for video processing or encoding. However, it is generally a time consuming and expensive process. Therefore, in many cases evaluation of video quality is done using objective measures, which may be poorly correlated with actual subjective results. In order to address this issue, we have developed VISTA (VIsual Subjective Testing Application), an easy to use application for visually comparing pairs of video sequences played synchronously side by side, and a user interface for indicating the relative subjective quality of the two video sequences. In addition, we developed a system for automating the evaluation process called Auto-VISTA. The system receives as input guidelines for the required testing session, prepares the content to be compared, launches the app in a crowdsourcing Internet marketplace (such as Amazon Mechanical Turk), and performs collection and analysis of the results. Thus, obtaining large scale subjective feedback becomes cheap and accessible, which in turn allows for fast and reliable evaluation cycles of different video encoding and processing solutions, or tuning various configurations and settings for a given solution.
Reaching an optimal trade-off between maximal perceptual quality of reconstructed video and minimal bitrate of the compressed video stream under a maximum bitrate constraint, for a wide variety of content, is a significant challenge and one that has major cost and user-experience implications for video content providers and consumers alike. This challenge is often addressed with content adaptive encoding, and generally strives to reach the optimal bit-rate per content at clip or scene level. Our solution presented herein, goes a step further, and performs encoder adaptation at the frame level. In this paper we describe our closed loop, optimized video encoder which performs encoding to the lowest bitrate which still preserves the perceptual quality of an encode to the target bitrate. The optimization is performed on a frame-by-frame basis, guaranteeing the visual quality of the video, in a manner that minimizes additional encoder complexity, thus making the solution applicable for live or real-time encoding. We also describe our subjectively tuned, low complexity, perceptual video quality metric which is the engine driving this solution.
The increasing quality and resolution of cellular phone cameras is creating a significant burden on mobile device storage
and network bandwidth requirements. In this paper we propose a novel method for recompressing digital photos, which
significantly reduces their file size, without affecting their spatial resolution or perceptual quality. By operating within
the scope of baseline JPEG, we ensure that the resulting image files can be viewed and edited with any software, browser
or consumer device. The proposed method is applied by iteratively recompressing the input image to varying degrees,
while computing the value of a novel, robust, perceptual image quality measure. When the image quality measure falls
within a pre-determined perceptual quality range, the iterative compression process ends and the resulting image is
output. This process ensures that the near maximum amount of compression, which still yields a perceptually identical
image, is applied to each input image. Subjective testing of obtained results has shown that using our proposed method,
the file size of photos may be reduced by a factor of up to 4X (75% reduction) without affecting their visual quality.
Feasibility of the proposed method for mobile applications has been established by implementation on the iPhone 3Gs
device.
The challenge of finding a reliable, real-time, automatic perceptual evaluation of image quality has been tackled
continuously by researchers worldwide. Existing methods often have high complexity, or are dependent on setup
specifics such as image size, or else have low correlation with subjective quality. We propose a novel, easy to compute,
image quality score which reliably measures artifacts introduced in block based coding schemes. The proposed score,
named BBCQ (Block Based Coding Quality) lies in the range 0-1 with 1 indicating identical images, and is composed of
three components. These components are based on a pixel-wise error using PSNR, evaluation of added artifactual edges
along coding block boundaries and a measure of the texture distortion. These three measures are calculated on image
tiles, whose size depends on image resolution, and are combined using a weighted geometric average. The obtained local
scores, one per image tile, may then be used for local quality evaluation, or pooled into a single overall image quality
score. The proposed quality score enables reliable, real-time, automatic perceptual evaluation of the quality of block-based
coded images. BBCQ has been successfully integrated into an automatic, perceptually lossless, JPEG
recompression system.
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