KEYWORDS: Video, Video compression, Computer programming, Video coding, Video processing, Distortion, Quantization, Standards development, RGB color model, Data processing
This paper presents a comparison of YUV color video formats using the H.264 video compression standard. The goal of this paper is to determine the best color video format for rate-distortion quality. This is a point of interest due to wireless video transmission quality and bandwidth limitations. The results show that for 1080p video, the YUV 4:2:0 video with a chrominance quantization parameter offset of zero is among the best performing color video format in terms of rate-distortion quality for three different levels of compression and two different entropy encodings.
As the cost of imaging systems have decreased, the quality and size has increased. This dynamic has made the practicality of many aerial imaging applications achievable such as cost line monitoring and vegetation indexing. Orthorectification is required for many of these applications; however, it is also expensive, computationally. The computational cost is due to oating point operations and divisions inherent in the orthorecti cation process. Two novel algorithm modi cations are proposed which signi cantly reduce the computational cost. The rst modi cation uses xed-point arithmetic in place of the oating point operations. The second replaces the division with a multiplication of the inverse. The result in an increase of 2x of the throughput while remaining within 15% of a pixel size in position.
An integer-based, post-compression rate-distortion optimization (PCRD-Opt) algorithm for JPEG2000 rate control is presented. The distortion estimation, described in the JPEG2000 standard, requires noninteger processing, and the overwhelming computational burden on JPEG2000 is the distortion calculation, which is calculated for every bit of the uncompressed image. An integer-based approach for distortion calculation is proposed. The proposed method reduces the computational requirements for PCRD-Opt within the Tier I encoder, as well as provides a more straightforward algorithm for embedded processing, requiring no distortion lookup tables (LUTs) for proper distortion computation. The proposed integer-based method improves upon the PCRD-Opt method described in the standard. Specifically, the proposed method reduces the Tier I processing time from a direct implementation of PCRD-Opt by approximately 39% on average and reduces the overall JPEG2000 processing by 34%. The proposed method reduces the Tier I processing time from an offline implementation of PDRD-Opt utilizing LUTs by approximately 21% on average, and reduces the overall JPEG2000 processing by 19%. The proposed integer-based distortion estimation provides a rate-distortion curve equivalent to both the direct and offline PCRD methods described in the standard.
Although optimal truncation of JPEG2000 compressed imagery provides an image of the highest quality per bit rate in terms of peak signal to noise ratio, the algorithm is highly computationally inefficient because of the removal of compressed image sections that have been previously calculated. The proposed idea utilizes a simple quantization technique prior to Tier I coding to remove many of the coding passes from the imagery that would not become a part of the final compressed bit stream. Two methods based on the this idea are discussed. The first method restricts the quantization value to be a power of 2, effectively eliminating the least significant bits of each code block through the quantization step. The second method relaxes the 2n restriction. Both methods give substantial reduction in computational complexity, a 39% and 46% reduction in overall complexity at 0.25 bits per pixel, respectively. The first method gives an equivalent rate distortion curve as traditional optimal truncation, and the second gives a similar rate distortion curve, only moderately underperforming traditional optimal truncation in a few images at few bit rates.
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