Fast encoding loss metric

Abstract

Provided is a process including: obtaining source and destination video data, the destination video data being a transformed version of the source video data; for a plurality of blocks in the given source frame, determining a respective source aggregate value that is based on a measure of central tendency of pixel values; for a plurality of blocks in the given destination frame, determining a respective destination aggregate value that is based on a measure of central tendency of pixel values; determining a plurality of differences between source and destination aggregate values; determining a frame aggregate value that is based on a measure of central tendency of the determined differences; and determining a measure of distortion of the destination video data based on the frame aggregate value.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This patent filing is a continuation of U.S. patent application Ser. No. 15 / 824,341, titled FAST ENCODING LOSS METRIC, filed 28 Nov. 2017, which claims the benefit of U.S. Provisional Patent App. 62 / 474,350, titled FAST ENCODING LOSS METRIC, filed 21 Mar. 2017, U.S. Provisional Patent App. 62 / 513,681, titled MODIFYING COEFFICIENTS OF A TRANSFORM MATRIX, filed 1 Jun. 2017, U.S. Provisional Patent App. 62 / 487,777, titled ON THE FLY REDUCTION OF QUALITY BY SKIPPING LEAST SIGNIFICANT AC COEFFICIENTS OF A DISCRETE COSINE TRANSFORM MATRIX, filed 20 Apr. 2017. The patent filing U.S. patent application Ser. No. 15 / 824,341, titled FAST ENCODING LOSS METRIC, filed 28 Nov. 2017 is also a continuation-in-part of U.S. patent application Ser. No. 15 / 447,755, titled APPARATUS AND METHOD TO IMPROVE IMAGE OR VIDEO QUALITY OR ENCODING PERFORMANCE BY ENHANCING DISCRETE COSINE TRANSFORM COEFFICIENTS, filed 2 Mar. 2017, which claims the benefit of U.S. Provis...

AI Technical Summary

Benefits of technology

This approach significantly reduces 'blocky' artifacts, enabling higher fidelity data transmission at a given bit-rate or better quality at lower bit-rates, without impairing compression effectiveness, and is compatible with existing decoders.

Problems solved by technology

Compression can, thus, be lossless or, when data is discarded, “lossy,” in the sense that some of the information is lost in the compression process.

At higher compression rates, however, a blocky artifact appears that is undesirable.

In some cases, this metric may be relatively computationally expensive, often requiring a relatively slow calculation on every pixel in an image (which is not to suggest that this attribute or any other is disclaimed in all embodiments).

As a result, it can be difficult to calculate these metrics on the fly and dynamically adjust compression, encoding, or decoding responsive to such metrics.

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