Comparison Research Of Atmospheric Correction Methods Of LANDSAT-7 ETM+ Image

Atmospheric interference can cause satellite remote sensing image blur, researches of how to construct a more precise reflectivity inversion model in order to restore geophysics reflectivity and further remove atmospheric interference as well as get a clear features image have been investigated for nearly 40 years. During this period there are different atmosphere correction methods. These methods have both advantages and disadvantages and all methods have scope of application themselves. Among these researches, few scholars put forward effective methods on correcting and evaluating the effects of atmospheric according to the design of Landsat 7 ETM+ image. Due to the wave bands ranging between near-infrared wavelengths and visual bands present an enormous proportion in satellite remote sensing image as well as act as the most severe atmospheric interference and image blurring bands, and furthermore become the true color imaging bands. Therefore it is urgent to explore a new ETM + image atmospheric effect correction method to reflect surface reflection more accurate in order to ultimately improve the quality of the images ETM + and heighten its value of applicationBased on former researches of domestic and overseas excellent achievements, by comparing in detail this paper finds a more accurate model—spectral vector analysis, which is for satellite remote sensing images atmospheric effect correction from visible to the near-infrared wavelengths. In experimental analysis, a cross radiation point spread function numerical algorithm between pixels is improved and the spectral vector continuous distribution space is accurately modeled. By adapting the discrete algorithm for realizing image atmosphere correction and comparing with other methods, e the results image precision and clarity can be further improved.This paper's basic structural framework is divided into six chapters as follow: The first chapter summarizes outlines the background and significance of the research and then briefly summarize the current research status of domestic and overseas. Meanwhile, this chapter also presents the contents and innovations in detail; The second chapter describes the atmosphere on the mechanism of electromagnetic radiation, the type and method of calculation; The third chapter analyzes remote sensing image atmospheric effect correction model from the standpoint of algorithm principle aspect and selects the optimization model to carry on further analysis to validly obtain the desired results which present higher precision on spectral vector space model obviously; The fourth chapter introduces spectral vector space atmosphere influence calibration methods and analyzes their algorithm theories in-depth as well as clarifies the theoretical basis and its solution methods; The fifth chapter adapts Landsat7 ETM + images as original experimental data to compare its results with the ATCOR2 model, and from which the Landsat7 ETM + method shows as better model, which has the precision like spectral vector analysis model and better speed of execution time as well as reduces one tenth of the original one, can be also obtained. At the same time, the spectral vector space storage structure is designed, which realizes the efficient index algorithm; The sixth chapter summarizes this experimental method briefly and puts forward the existing problems according to what mentioned above, furthermore, prospective of the model is also looked forward.