Data compression with finite windows
Communications of the ACM
Linear Algorithm for Data Compression via String Matching
Journal of the ACM (JACM)
Data compression via textual substitution
Journal of the ACM (JACM)
Information Sciences: an International Journal - Dictionary based compression
JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Inplace 2D matching in compressed images
Journal of Algorithms
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
IEEE Transactions on Image Processing
On the distribution function of the complexity of finite sequences
Information Sciences: an International Journal
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Dictionary-based compression methods are a popular form of data file compression. LZ77, LZ78 and their variants are likely the most famous of these methods. These methods are implemented to reduce the one-dimensional correlation in data, since they are designed to compress text. Therefore, they do not take advantage of the fact that, in images, adjacent pixels are correlated in two dimensions. Previous attempts have been made to linearize images in order to make them suitable for dictionary-based compression, but results show that no single linearization is best for all images. In this paper, a true two-dimensional dictionary-based lossless image compression scheme for grayscale images is introduced. Testing results show that the compression performance of the proposed scheme outperforms and surpasses any other existing dictionary-based compression scheme. The results also show that it slightly outperforms JPEG-2000's compression performance, when it operates in its lossless mode, and it is comparable to JPEG-LS's compression performance, where JPEG-2000 and JPEG-LS are the current image compression standards.