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Remote Sensing Image Compression in Visible Near-Infrared Range Using Heterogeneous Compressive Sensing
Li, J.; Fu, Y.; Li, G. N.; Liu, Z. L.
2018
Source PublicationIeee Journal of Selected Topics in Applied Earth Observations and Remote Sensing
ISSN1939-1404
Volume11Issue:12Pages:4932-4938
AbstractCompressive sensing (CS) framework is very suitable for onboard image compression of high-resolution remote sensing cameras in the visible/near-infrared range (VI/NI-RSC) because it has the low-complexity in the sampling measurement stage. In this paper, we propose a new heterogeneous CS method for VI/NI-RSCs. Different from conventional CS methods evenly allocating sensing resources, the proposed method fully employs texture-feature information of remote sensing images to guide the allocation of sensing resources. More sensing resources are allocated to high-frequency regions, but fewer to low-frequency regions. The heterogeneous distribution of sensing resources obtains high reconstruction quality at the same compression performance, as well as high compression performance at the same level reconstructed quality. The shift of sensing resources is consistent with artificial image interpretations, i.e., human visual characteristics, where high-frequency regions, such as edges and textures, are the principal proof of the ground target identification. Experimental results indicate that the proposed method has better reconstruction quality than conventional CS method where texture-features are not utilized.
KeywordHeterogeneous compressive sensing (CS) panchromatic images remote sensing image compression information Engineering Physical Geography Remote Sensing Imaging Science & Photographic Technology
DOI10.1109/jstars.2018.2879363
Indexed BySCI ; EI
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Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ciomp.ac.cn/handle/181722/61129
Collection中国科学院长春光学精密机械与物理研究所
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GB/T 7714
Li, J.,Fu, Y.,Li, G. N.,et al. Remote Sensing Image Compression in Visible Near-Infrared Range Using Heterogeneous Compressive Sensing[J]. Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing,2018,11(12):4932-4938.
APA Li, J.,Fu, Y.,Li, G. N.,&Liu, Z. L..(2018).Remote Sensing Image Compression in Visible Near-Infrared Range Using Heterogeneous Compressive Sensing.Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing,11(12),4932-4938.
MLA Li, J.,et al."Remote Sensing Image Compression in Visible Near-Infrared Range Using Heterogeneous Compressive Sensing".Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing 11.12(2018):4932-4938.
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