Manipulating lossless video in the compressed domain

Abstract

A compressed-domain transformation is one that operates directly on the compressed format, rather than requiring conversion to an uncompressed format prior to processing. Performing operations in the compressed domain offers large speedups, as it reduces the volume of data processed and avoids the overhead of re-compression.While previous researchers have focused on compressed-domain techniques for lossy data formats, there are few techniques that apply to lossless formats. In this paper, we present a general technique for transforming lossless data as compressed with the slidingwindow Lempel Ziv algorithm (LZ77). We focus on applications in video editing, where our technique supports color adjustment, video compositing, and other operations directly on the Apple Animation format (a variant of LZ77).We implemented a subset of our technique as an automatic program transformation. Using the StreamIt language, users write a program to operate on uncompressed data, and our compiler transforms the program to operate on compressed data. Experiments show that the technique offers speedups roughly proportional to the compression factor. For our benchmark suite of 12 videos in Apple Animation format, speedups range from 1.1x to 471x, with a median of 15x.

Lempel-Ziv Factorization in Linear-Time O(1)-Workspace for Constant Alphabets

“…Lempel-Ziv factorization (LZ77) [1] of a string has been widely used in string processing, genome sequence alignments [2], [3], text indexes [4], data compression and decompression [5]- [8], etc. Especially, compression schemes based on LZ77 can be particularly good at processing the modern datasets with highly repetitive characteristics in recent years.…”

Improving a lightweight LZ77 computation algorithm for running faster

“…The Lempel–Ziv factorization (LZ77) , named after its authors Abraham Lempel and Jacob Ziv, is an important concept in computer science. Because of its high efficiency in string processing, it has been widely used in many applications such as file compression , pattern discovery, sequence alignments, and full‐text indexes . Very recently, several powerful instances have testified that compression schemes based on LZ77 are effective in modern datasets, especially in the collections of highly repetitive characteristics such as Genome sequences .…”