中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Hybrid Constraints of Pure and Mixed Pixels for Soft-Then-Hard Super-Resolution Mapping With Multiple Shifted Images

文献类型:SCI/SSCI论文

作者Chen Y. H.; Ge, Y.; Heuvelink, G. B. M.; Hu, J. L.; Jiang, Y.
发表日期2015
关键词Hybrid constraints multiple shifted images (MSIs) remotely sensed imagery super-resolution mapping (SRM) hopfield neural-network remote-sensing imagery markov-random-field land-cover sensed imagery spatial-resolution hyperspectral imagery contouring methods attraction model subpixel scale
英文摘要Multiple shifted images (MSIs) have been widely applied to many super-resolution mapping (SRM) approaches to improve the accuracy of fine-scale land-cover maps. Most SRM methods with MSIs involve two processes: subpixel sharpening and class allocation. Complementary information from the MSIs has been successfully adopted to produce soft attribute values of subpixels during the subpixel sharpening process. Such information, however, is not used in the second process of class allocation. In this paper, a new class-allocation algorithm, named "hybrid constraints of pure and mixed pixels" (HCPMP), is proposed to allocate land-cover classes to subpixels using MSIs. HCPMP first determines the classes of subpixels that overlap with the pure pixels of auxiliary images in MSIs, after which the remaining subpixels are classified using information derived from the mixed pixels of the base image in MSIs. An artificial image and two remote sensing images were used to evaluate the performance of the proposed HCPMP algorithm. The experimental results demonstrate that HCPMP successfully applied MSIs to produce SRM maps that are visually closer to the reference images and that have greater accuracy than five existing class-allocation algorithms. Especially, it can produce more accurate SRM maps for high-resolution land-cover classes than low-resolution cases. The algorithm takes slightly less runtime than class allocation using linear optimization techniques. Hence, HCPMP provides a valuable new solution for class allocation in SRM using auxiliary data from MSIs.
出处Ieee Journal of Selected Topics in Applied Earth Observations and Remote Sensing
8
5
2040-2052
收录类别SCI
语种英语
ISSN号1939-1404
源URL[http://ir.igsnrr.ac.cn/handle/311030/38418]  
专题地理科学与资源研究所_历年回溯文献
推荐引用方式
GB/T 7714
Chen Y. H.,Ge, Y.,Heuvelink, G. B. M.,et al. Hybrid Constraints of Pure and Mixed Pixels for Soft-Then-Hard Super-Resolution Mapping With Multiple Shifted Images. 2015.

入库方式: OAI收割

来源:地理科学与资源研究所

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