More efficient ground truth ROI image coding technique: implementation and wavelet based application analysis

作     者：KUMARAYAPA Ajith 

作者机构：Department of Electronics and Communication Engineering Harbin Institute of Technology Harbin 150001 China 

出 版 物：《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》 (浙江大学学报（英文版）A辑（应用物理与工程）)

年 卷 期：2007年第8卷第6期

页      面：835-840页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 081001[工学-通信与信息系统] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Project (No. 2004144013) supported by the Chinese Government Scholarship Council  China 

主　　题：Smooth low texture remote sensing (SLTRS) image Modified region of interest (ROI) image codec Wavelet filters Low bit rate (LBR). High bit rate (HBR). ROI coding 

摘      要：In this paper, more efficient, low-complexity and reliable region of interest （ROI） image codec for compressing smooth low texture remote sensing images is proposed. We explore the efficiency of the modified RO! codec with respect to the selected set of convenient wavelet filters, which is a novel method. Such ROI coding experiment analysis representing low bit rate lossy to high quality lossless reconstruction with timing analysis is useful for improving remote sensing ground truth surveillance efficiency in terms of time and quality. The subjective [i.e. fair, five observer （HVS） evaluations using enhanced 3D picture view Hyper memory display technology] and the objective results revealed that for faster ground truth ROI coding applications, the Symlet-4 adaptation performs better than Biorthogonal 4.4 and Biorthogonal 6.8. However, the discrete Meyer wavelet adaptation is the best solution for delayed ROI image reconstructions.