Dissertation > Excellent graduate degree dissertation topics show

Image denoising based on Wavelet and based on finite ridgelet transform

Author: CaiZheng
Tutor: TaoShaoHua
School: Central South University
Course: Electronic Science and Technology
Keywords: the wavelet transform the ridge transform imagede-noising PSNR (peak signal to noise ratio)
CLC: TP391.41
Type: Master's thesis
Year: 2012
Downloads: 59
Quote: 0
Read: Download Dissertation


Image de-noising is a process which preserves important image information and removes image noise as much as possible. Image de-noising is a necessary step of image analysis, whose performance is directly dependent on the performance of image de-noising, so image de-noising is one of the most important aspects in the image processing field. The wavelet de-noising method is a kind of image de-noising methods, which can achieve good de-noising performance. But the wavelet transform is not good at processing line singularities or surface singularities, so researchers have proposed the finite ridgelet transform to improve the default of the wavelet transform.The paper will improve the de-noising performance of the wavelet de-noising methods from two aspects. One is the relation of wavelet coefficients, and the other is that the wavelet can’t process line singularities well.The paper focuses on the faults of the method considering the neighborhood dependencies of the wavelet coefficients and the method considering the inter-scale dependencies of the wavelet coefficients, and then proposes a de-noising method, which takes the inter-scale and neighborhood dependencies of wavelet coefficients into account. The proposed method uses the correlation of wavelet coefficients and the average magnitudes of the surrounding wavelet coefficients within a local window to describe the intra-scale and neighborhood dependencies of wavelet coefficients respectively. Based on the two dependencies, the paper proposes a new threshold function and researches the relation between the threshold and image noise standard deviation. Experiments show that compared with the method considering the neighborhood dependencies of the wavelet coefficients and the method considering the inter-scale dependencies of the wavelet coefficients, the proposed method can achieve higher PSNRs.In order to improve the fault that the wavelet transform can not process line singularities well, the paper proposes an image de-noising method combining the wavelet and the finite ridgelet transforms. First, the proposed method divides the whole image into image blocks, and then the homogenous blocks and non-homogenous blocks are selected and processed by the wavelet de-noising method and the finite ridgelet de-noising method, respectively. Based on the histogram of the standard deviation of image blocks, the paper proposes a selection rule of the homogenous blocks. Compared with the wavelet de-noising method using Bayes rule and the finite ridgelet de-noising method with Bayes rule, the de-noising performance of the proposed method is better. When the added noise standard deviation is above20, the SNRs of the proposed method can increase by1db.

Related Dissertations

  1. Feature Extraction, Selection and Combination in Lipreading,TP391.41
  2. Research on Identification System of Cashmere and Wool Fiber,TS101.921
  3. Characteristics of sensory stimulation evoked,R318.0
  4. Network transmission ROI image coding algorithm,TN919.81
  5. Wavelet Transform with Applications in Data Processing of Bridge’s Deformation Observation,TP274
  6. Based on Contourlet Transform Digital Watermarking Method,TP309.7
  7. Image Fusion Algorithms Based on Multi-scale Analysis,TP391.41
  8. Feature Extraction Technologies Research and Implementation of 3D Models Based on Wavelet Transform,TP391.41
  9. An Algorithm on Clustering and Anomaly Detection for Multiple Data Streams,TP311.13
  10. Research on Information Hiding Based on Images,TP309.7
  11. Design and Implication of Image Compression System Based on Wavelet and DM6446,TP391.41
  12. Research on Three-dimensional Surface Splicing Method Based on Genetic Algorithm and the Wavelet Transformation,TP391.41
  13. Study on Medical Image Segmentation Method Based on Parametric Active Contour Models,TP391.41
  14. SOPC Design of Transient Power Quality Disturbances Detecting Based on Nios Ⅱ,TN47
  15. Based on Lifting Scheme Wavelet Packet Transform and Artificial Neural Network Wing-box Multi-damage Detection,V224
  16. An Empirical Study on the Relationship between the China Stock Index Futures and Spot Markets,F224
  17. Research on Design and Data Processing for Wireless Electrocardiogram Monitoring Systems,TP274
  18. The Study of Vibration Signal Analysis System Based on Wavelet Fractal Theory,TN911.6
  19. Research and Realization of Image Denoising Based on Wavelet Transform,TP391.41
  20. A Study Regarding to Organizational Identification and Simulation of Reality for Double-Organization Fabric,TS105
  21. Data Compression and De-noising of Power Quality Transient Signals,TM711

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