期刊
JOURNAL OF REAL-TIME IMAGE PROCESSING
卷 19, 期 1, 页码 173-183出版社
SPRINGER HEIDELBERG
DOI: 10.1007/s11554-021-01173-0
关键词
Approximate KLT; Image compression; Karhunen-Loeve transform; Low-complexity transforms
类别
资金
- CoordenacAo de Aperfeicoamento de Pessoal de Nivel Superior (CAPES)
- Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)
- FundacAo de Amparo a Ciencia e Tecnologia de Pernambuco (FACEPE), Brazil
The paper introduces a new class of low-complexity transforms obtained through applying the round function to KLT matrix elements, which perform well in image compression with low implementation cost.
The Karhunen-Loeve transform (KLT) is often used for data decorrelation and dimensionality reduction. Because its computation depends on the matrix of covariances of the input signal, the use of the KLT in real-time applications is severely constrained by the difficulty in developing fast algorithms to implement it. In this context, this paper proposes a new class of low-complexity transforms that are obtained through the application of the round function to the elements of the KLT matrix. The proposed transforms are evaluated considering figures of merit that measure the coding power and distance of the proposed approximations to the exact KLT and are also explored in image compression experiments. Fast algorithms are introduced for the proposed approximate transforms. It was shown that the proposed transforms perform well in image compression and require a low implementation cost.
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