Research On Super Resolution Method Of Remote Sensing Image In Target Recognition

In1972,the United States launched the first earth observation satellite-landsat1,which marked the human entered the new era of remote sensing.With the rapiddevelopment of remote sensing technology and the widespread application,although theresolution of the remote sensing image has been improving but still difficult to meet theneeds of many areas for high resolution remote sensing image,such as during smalltarget in remote sensing image (planes,ships,Bridges,etc.) to identify,we need to find thetarget level is usually m and use of the existing remote sensing images for small targetsegmentation accuracy is low. Improve the resolution of remote sensing images can beimproved to hardware implementation,but the more elaborate have the craft level,costwill be high,and imaging equipment improved space is limited,people started to try themethod of using software to solve this problem,super-resolution reconstructiontechnology arises under the background of this historic moment.Based on super-resolution reconstruction technology improve the resolution of theexisting remote sensing images,this paper proposes a super-resolution reconstructionmethods based on,to provide target segmentation contains more abundant features ofremote sensing image data source effectively,the super-resolution reconstructiontechnology for small target recognition,and through the experiment (dam) small target isput forward successfully.In this paper,the super-resolution reconstruction of key technology to do a thoroughresearch,mainly includes the following aspects:Remote sensing image registration,the high accuracy of image registration is thebasis of Super-resolution reconstruction,this paper introduces the now commonly usedimage registration technique,and analyses the existing difficulties in registration ofremote sensing technology,direct at the particularity of the remote sensing image of thesmall target use a multispectral remote sensing image registration method based onSIFT,through those experiments in this paper,we find the method can fast andautomatically complete the high accuracy.Remote sensing image super-resolution reconstruction,the current sequencesuper-resolution algorithm is mainly divided into two categories,airspace andfrequency domain method. This paper summarizes the principle and advantages of the main algorithm of two methods,and put forward a kind of super resolutionreconstruction algorithm based on Hopfield neural network,in the remote sensingimage super-resolution reconstruction results,we often prone to detail such as theboundary of the image blur,and these part contains more important information,thismethod can effectively improve the ability of detail protection,through the experimentcan make better effect on super resolution.The super-resolution technology used in small target segmentation,thesegmentation accuracy of the small target segmentation not only depends on the targetmethod,high resolution remote sensing image as the source data is also one of theimportant factors,high resolution remote sensing images can provide more effectivefeature for target identification,improve the identification accuracy. In this paper,theapplication of super-resolution technique to target segmentation,which finished thesmall targets (dam) recognition through the experiment.