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
An algorithmic study on lossless image compression
DCC '96 Proceedings of the Conference on Data Compression
Inplace 2D matching in compressed images
Journal of Algorithms
Revisiting dictionary-based compression: Research Articles
Software—Practice & Experience
A universal algorithm for sequential data compression
IEEE Transactions on Information Theory
Compression of individual sequences via variable-rate coding
IEEE Transactions on Information Theory
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
IEEE Transactions on Image Processing
2D-pattern matching image and video compression: theory, algorithms, and experiments
IEEE Transactions on Image Processing
Wavelet based color image compression using vector quantization and morphology
Proceedings of the International Conference on Advances in Computing, Communication and Control
Scanned compound document encoding using multiscale recurrent patterns
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
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Dictionary-based encoding methods are popular forms of data compression. These methods were initially 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 adjacent pixels in images are correlated in two dimensions. Previous attempts have been made to adapt dictionary-based compression schemes to consider the two-dimensional nature of images, but mostly for binary images. In this paper, a two-dimensional dictionary-based lossless image compression scheme for grayscale images is introduced. The proposed scheme reduces correlation in image data by finding two-dimensional blocks of pixels that are approximately matched throughout the data and replacing them with short codewords. Test results show that the compression performance of the proposed scheme outperforms and surpasses any other existing dictionary-based lossless compression scheme. The results also show that it slightly outperforms JPEG-2000s compression performance, when it operates in its lossless mode, and it is comparable to JPEG-LS's and CALIC's compression performance, where JPEG-2000 and JPEG-LS are the current image compression standards, and CALIC is a Context-based Adaptive Lossless Image Coding scheme.