The piecewise-constant image model (PWC) is a new technique for lossless compression of palette images. PWC is a blend of traditional scanline-oriented and newer object-based methods. Remarkably, PWC delivers the best...
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The piecewise-constant image model (PWC) is a new technique for lossless compression of palette images. PWC is a blend of traditional scanline-oriented and newer object-based methods. Remarkably, PWC delivers the best known compression across a wide variety palette of image types while delivering translation speeds comparable to highly tuned one-dimensional methods. This paper introduces the topic of palette image coding and traces the development of the piecewise-constant model from a completely object-oriented code requiring two image passes to a high-performance scanline-oriented code.
Free Lossless Audio Codec (FLAC) format is a widely used format for audio storage. Using a lower performance single threaded approach, FLAC is easily decoded faster than the rate at which it is played at. However, if ...
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ISBN:
(纸本)9781728111414
Free Lossless Audio Codec (FLAC) format is a widely used format for audio storage. Using a lower performance single threaded approach, FLAC is easily decoded faster than the rate at which it is played at. However, if you wish to transcode or edit long FLAC audio files then decoding times using single thread CPU approaches becomes significant. The FLAC format contains a sequence of frames, these frames vary in size so start locations are unknown until the previous frame is decoded. This complicates parallelizing decoding. However, frames start with known fixed bit patterns and each frame contains a frame index, it is possible to locate and decode frames in parallel. In this paper, we present an approach that exploits this characteristic enabling all the frames to be decoded in parallel. This approach is implemented and evaluated using an NVIDIA GeForce (R) GTX 1080 graphics card showing a 5 times performance improvements than the widely used official implementation running on an Intel Core T i7-6770K CPU.
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