JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
Compression of facial images using the K-SVD algorithm
Journal of Visual Communication and Image Representation
Double sparsity: learning sparse dictionaries for sparse signal approximation
IEEE Transactions on Signal Processing
Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing
Sparse and Redundant Representations: From Theory to Applications in Signal and Image Processing
-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation
IEEE Transactions on Signal Processing
Signal Recovery From Random Measurements Via Orthogonal Matching Pursuit
IEEE Transactions on Information Theory
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
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In this work, we introduce a new content-adaptive compression scheme, called image primitive coding, which exploits the input image for training a dictionary. The atoms composed of the learned dictionary are named as image primitives. The coding performance between the learned image primitives and the traditional DCT basis is compared, and demonstrates the potential of image primitive coding. Furthermore, a novel concept, entropy of primitives (EoP), is proposed for measuring image visual information. Some very interesting results about EoP are achieved and analyzed, which can be further studied for visual quality assessment.