Dissertation > Excellent graduate degree dissertation topics show

Research on Image Denoising with Wavelet Transform

Author: YanBing
Tutor: WangJinHe
School: Qingdao Technological University
Course: Applied Computer Technology
Keywords: Wavelet Transform Denoising Mean Filtering Threshold function Threshold
CLC: TP391.41
Type: Master's thesis
Year: 2010
Downloads: 138
Quote: 1
Read: Download Dissertation

Abstract


Image denoising technology as an important part of the signal processing and modern communications , and people are getting closer . In practical applications, it is often used as the preprocessing of the image processing and recognition is the subsequent higher-level analysis of the image , the foundation processing . The wavelet transform is a development based on Fourier transform time-frequency analysis method is an effective analytical tool , it has low entropy , multi-resolution , go to the relevant election based flexible characteristics and in the the signal has the advantage that makes it widely applied in the field of image processing . Among them, the use of the wavelet transform of the noisy image signal processing , while retaining the high-frequency information can effectively filter out the noise , get the best recovery of the original image signal Traditional wavelet threshold denoising method can suppress noise to some extent , but there are varying degrees of image blur . This paper presents two wavelet image denoising methods : one is based on the mean filter and wavelet transform image denoising method combining these two methods combined can make full use of their respective advantages , to better improve the filtering performance , but also can suppress the noise of the image at the same time to maintain the edge information is an effective method for image denoising ; another for the shortcomings of traditional threshold function improved on the traditional wavelet threshold functions , based on image singular characteristics of a new wavelet contraction threshold . The matlab simulation experiment , and several other methods of comparative analysis , the results demonstrate the feasibility , effectiveness and superiority of the improved image denoising method presented in this paper .

Related Dissertations

  1. Research on Electromagnetic Acoustic Transducer Detection System Based on FPGA,TH878.2
  2. Resrarch on Multisignatures and Multisigncryptions from Identity-based,TN918.1
  3. Research on Spread Spectrum Code Acquisition of Double Threshold Based on Sliding Correlator,TN914.42
  4. Performance Analysis of Anti-Multipath Capability in DSSS System and Study on the Compensation Methods,TN914.42
  5. Research on Methods of Medical Ultrasound Image Denoising,TP391.41
  6. Feature Extraction, Selection and Combination in Lipreading,TP391.41
  7. Design of Testing Equipment for Electronic Products,TN06
  8. Citrus Image Segmentation Based on Genetic Algorithm,TP391.41
  9. Research on Identification System of Cashmere and Wool Fiber,TS101.921
  10. Macroinvertebrate Assemblages and Its Application in the Water Management,X824
  11. Bioavailability of Phthalic Acid Esters in Different Types of Soil-plant Systems,X53
  12. Characteristics of sensory stimulation evoked,R318.0
  13. Differences in different populations compared proprioception and Brain Mechanisms,B845
  14. Subliminal subliminal anxiety of material of different emotional cues students Inhibition of Return,B842
  15. Mobile WSN data collection based on the virtual cluster head Strategy,TP212.9
  16. Network transmission ROI image coding algorithm,TN919.81
  17. Image Fusion Algorithms Based on Multi-scale Analysis,TP391.41
  18. Feature Extraction Technologies Research and Implementation of 3D Models Based on Wavelet Transform,TP391.41
  19. Research on Contourlet Transform and Its Application on Image Processing,TP391.41
  20. Research on Face Detection Based on Skin Color Segmentation and AdaBoost Algorithm,TP391.41
  21. An Algorithm on Clustering and Anomaly Detection for Multiple Data Streams,TP311.13

CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
© 2012 www.DissertationTopic.Net  Mobile