Abstract: In an example method, one or more processing devices receive encoded image data, and cause visual content to be presented on a display device according to the encoded image data. Further, the one or more processing devices receive measurement data regarding the visual content presented on the display device, and determine, based on the measurement data, one or more first perceptual quantizer (PQ) codes corresponding to the visual content presented on the display device. Further, the one or more processing devices determine, based on the encoded image data, one or more second PQ codes, and determine one or more metrics indicative of a performance characteristic the display device based on the first PQ codes and the second PQ codes. The one or more processing devices store a data item including the one or more metrics.

Abstract: In an example method, one or more processing devices receive encoded image data, and cause visual content to be presented on a display device according to the encoded image data. Further, the one or more processing devices receive measurement data regarding the visual content presented on the display device, and determine, based on the measurement data, one or more first perceptual quantizer (PQ) codes corresponding to the visual content presented on the display device. Further, the one or more processing devices determine, based on the encoded image data, one or more second PQ codes, and determine one or more metrics indicative of a performance characteristic the display device based on the first PQ codes and the second PQ codes. The one or more processing devices store a data item including the one or more metrics.

Abstract: A video quality assessment method may include frame-by-frame analysis of a test video sequence (often compressed) with its original (reference) counterpart, pre-conditioning elements of the test and reference frames, defining a region of interest in the pre-conditioned test frame and estimating relative errors within the region of interest between the test and reference frame, filtering the estimated errors of the region of interest temporally across adjacent frames within a perpetually relevant time window, aggregating the filtered errors within the time window, ranking the aggregated errors, selecting a subset of the ranked errors, aggregating across the selected subset of errors, and inputting said aggregated error to a quality assessment system to determine a quality classification along with an estimated quality assessment.

Abstract: A video quality assessment method may include frame-by-frame analysis of a test video sequence (often compressed) with its original (reference) counterpart, pre-conditioning elements of the test and reference frames, defining a region of interest in the pre-conditioned test frame and estimating relative errors within the region of interest between the test and reference frame, filtering the estimated errors of the region of interest temporally across adjacent frames within a perpetually relevant time window, aggregating the filtered errors within the time window, ranking the aggregated errors, selecting a subset of the ranked errors, aggregating across the selected subset of errors, and inputting said aggregated error to a quality assessment system to determine a quality classification along with an estimated quality assessment.

Abstract: Video compression and decompression that produces a desirable balance of compression rate and picture quality while, at the same time, reducing an average number of computational cycles required to achieve the desired picture quality and compression rate. Also disclosed are video processing platforms, systems and methods that produce a quality and bits per frame performance for more widespread use of video data exchanges using standardized computer architectures, such as cellular phones having non-video optimized processing platforms.