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In this paper, we propose a novel remote sensing image compression method based on double-sparsity dictionary learning and universal trellis coded quantization (UTCQ). Recent years have seen a growing interest in the study of natural image compression based on sparse representation and dictionary learning. We show that using the double-sparsity model to(More)
The development of objective image quality assessment (IQA) metrics aligned with human perception is of fundamental importance to numerous image-processing applications. Recently, human visual system (HVS)-based engineering algorithms have received widespread attention for their low computational complexity and good performance. In this paper, we propose a(More)
The development of reliable objective image quality assessment (IQA) metrics coordinate to the human‟s perception is crucial in numerous image processing applications. State-of-art perceptual IQA methods focus on two techniques using the sensitivities of human visual system (HVS). One is perceptual pooling strategy in spatial domain while the other is(More)
Multi-channel peculiarity is one of the most widely accepted human visual system (HVS) models for perceptual image quality assessment (IQA). Otherwise than extensive studies of channel decomposition and intra-channel distortion measure, relatively scant research effort has been devoted to develop efficient multichannel evaluation pooling strategies. In this(More)
People are sharing, transmitting and storing millions of images every day. To store images it may require huge data storage. The compression of images reduces the storage required to store images, also permits the faster transmission. Several works have been carried out in designing compression techniques that reduce image size with higher image quality.(More)
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