Dissertation > Excellent graduate degree dissertation topics show
On Technology of Inpainting for Remote Sensing Image
Author: ChenLu
Tutor: GengZeXun
School: PLA Information Engineering University
Course: Photogrammetry and Remote Sensing
Keywords: Remote Sensing Image Image inpainting Partial Differential Equation (PDE) Texture Synthesize
CLC: TP751
Type: Master's thesis
Year: 2011
Downloads: 48
Quote: 0
Read: Download Dissertation
Abstract
|
Remote sensing images are very important to the national defense and economic development, and have extensive applications in surveying and mapping, environment monitoring, resources exploring and so on. The processing and application of remote sensing images face a lot of problems that should be solved necessarily. And among them, there are two problems influencing image using. The first one is image information imperfection instauration problems such as image pixel dead or pixel block lost; the other one is to remove the information such as markings, writings, secret objects existing on the image those are redundant or inconvenience for image using. Image inpainting is a technique used for recovering damaged images, removing or camouflaging redundant information. This thesis focuses on the remote sensing image inpainting problem. The main contents include the following:1. Giving a summary of a variety of inpainting problems in remote sensing images, and then carry on some extension; some important theories such as Bayesian principle, spread principle, variation principle, image gradient and difference method involved in image inpainting are introduced, that lay the foundation for my coming research.2. PDE-based image inpainting models including BSCB, TV and CDD are investigated. A new algorithm by combining with convolution-based inpainting and CDD inpainting is proposed. Experiments show that the proposed algorithm meets the results of CDD inpainting and is able to archive faster results than convolution-based inpainting.3. Exemplar-based image inpainting is investigated in detail. And Criminisi inpainting method is optimized. The realization of the optimized algorithm shows a good result for removing important objects in the remote sensing image. And this way present a good way to realize remote sensing image used in both army and civilian. Getting out of the secret of a digital raster graphic is achieved in this method successfully, and also aerial photo sheet number information.
|
Related Dissertations
- Study of Remote Sensing Image Parallel Processing Algorithms Based on GPU and Optimization Techniques,TP751
- Multi-spectral remote sensing image registration and fusion research,TP751
- The human ear to identify a number of Algorithm,TP391.41
- Research on Image Impainting and Completion,TP391.41
- Image edge detection the repair algorithm technology research,TP391.41
- Research on Remote Sensing Image Processing Combining High Fidelity Compression and Resolution Enhancement,TP751
- Radial Basis Function Meshless Collocation Method for Partial Differential Equation,O241.82
- The Research on Digital Image Inpainting Algorithm Based on Texture Synthesis,TP391.41
- Research on Transform Domain Image Level Correlation Analysis Based Remote Sensing Images Fusion Method,TP751
- Image Inpainting Based on Sparse Representation,TP391.41
- The Landscape Dynamic Analyzing of the Area along the Yangtze River in Jiangsu Based on RS and GIS,S771.8
- Classification of Hyperspectral Remote Sensing Image Based on the Cloud Model Theory,TP751
- Forest Edge Detection Based on High Spatial Resolution Remote Sensing Imagery and Wavelet Analysis,TP751
- Application of Non-negative Matrix Factorization Metho in Remote Sensing Image Recognition,TP751
- Research on Space-Borne Multi-Sensor Image Fusion Based on Non-Negative Matrix Factorization,TP751
- Research of Remote Sensing Image Fusion Based on Multi-Wavelet Transform,TP751
- Data Mining for Forest Space Information Features from Remote Sensing Images,TP751
- Study on the Spatial-temporal Change of Vegetation in Zhejiang Province and the Landscape Regeneration Design of Forest,Q948
- Applicability Analysis of Region Multi-center Method for Rs Imagery Classification,P237
- Denoising and Cloud Shadow Removing of Remote Sensing Image Based on Contourlet Transform,TP751
- Research on Cloud Detection and Removal of Remote Sensing Image,TP751
CLC: > Industrial Technology > Automation technology,computer technology > Remote sensing technology > Interpretation, identification and processing of remote sensing images > Image processing methods
© 2012 www.DissertationTopic.Net Mobile
|