TAILIEUCHUNG - Lecture Digital image processing - Lecture 19: Image restoration

This chapter presents the following content: Image restoration techniques, difference between image enchantment and image restoration, image formation process and the degradation model, degradation model in continues function and its discrete formulation, discrete formulation for 1D and 2D. | Digital Image Processing CSC331 Image restoration 1 Summery of previous lecture Image Enhancement techniques Spatial domain techniques Pont processing techniques Mask Processing techniques Frequency domain techniques Ideal and Butterworth lowpass filter Ideal and Butterworth highpass filer Gaussian filter Homemorphic filter 2 Todays lecture Image restoration techniques Difference between image enchantment and image restoration Image formation process and the degradation model Degradation model in continues function and its discrete formulation Discrete formulation for 1D and 2D 3 Objectives of Image Restoration 4 Overview of restoration techniques 5 Degradation model 6 Definitions 7 Defining linearity (Super position theorem) 8 Homogeneity property 9 Degradation model in case of continuous functions 10 11 Impulse response (point spread function) 12 H as position invariant 13 Discrete formulation degradation model First in case of 1 dimension and later it will be extend to 2 dimensional cases for digital image processing operations. For simplicity, initially, we will neglect the contribution of the noise term that is eta (x, y). 14 15 16 17 2D Discrete formulation degradation model 18 19 20 Summery of the lecture Image restoration techniques Difference between image enchantment and image restoration Image formation process and the degradation model Degradation model in continues function and its discrete formulation Discrete formulation for 1D and 2D 21 References Prof .P. K. Biswas Department of Electronics and Electrical Communication Engineering Indian Institute of Technology, Kharagpur Gonzalez R. C. & Woods . (2008). Digital Image Processing. Prentice Hall. Forsyth, D. A. & Ponce, J. (2011).Computer Vision: A Modern Approach. Pearson Education. .

• Đồ họa - Thiết kế - Flash
• Image restoration
• Digital image processing
• Lecture Digital image processing
• Digital images
• Digital computers
• Image processing
• Blind deconvolution
• Blind method
• Degradation model
• Restoration techniques
• Restoration techniques
• Gaussian noise
• Erlang(Gama) noise
• Exponential noise
• Image Restoration Matrix Formulation
• Constrained least squares filtering
• Brief review of matrix differentiation
• Pseudo inverse Filtering
• Parametric Wiener Filter
• International Journal of computer science & communication networks
• Satellite image enhancement and restoration
• Satellite image enhancement
• Conventional image processing
• Soft computing techniques
• Support Package for Digital Image Processing
• Digital Image Fundamentals
• Intensity Transformations
• Spatial Filtering
• Multidimensional Signals
• Analogue
• Digital Image Representation
• Imaging Systems
• Planar X Ray Imaging
• Data Sources
• Image Representation
• image communication
• robotics
• geoscience
• Image Enhancement
• Matlab
• case studies
• image segmentation
• edge detection
• restoration
• dilation & erosion
• Tự động hóa
• Điện – điện tử
• Cơ khí chế tạo máy
• Kiến trúc xây dựng
• kỹ thuật viễn thông
• áo cáo hóa học
• báo cáo hóa học
• công trình nghiên cứu về hóa học
• tài liệu về hóa học
• cách trình bày báo cáo
• báo cáo toán học
• tài liệu báo cáo nghiên cứu khoa học
• kiến thức toán học
• các báo cáo toán học hay
• báo cáo khoa học
• Attenuation correction
• Confocal microscopy
• Calculus of variations
• Confocal microscopic data
• mobile computing
• Program Design
• Algorithm Development
• Logical Vectors
• computer graphics
• algorithms techniques