Shape from Shading Based on Lax-Friedrichs Fast Sweeping and Regularization Techniques With Applications to Document Image Restoration

2007 ◽  
Author(s):  
Li Zhang ◽  
Andy M. Yip ◽  
Chew Lim Tan
Keyword(s):  
Image Restoration ◽  
Shape From Shading ◽  
Document Image ◽  
Fast Sweeping ◽  
Regularization Techniques

Faxed document image restoration method based on local pixel patterns

1998 ◽  
Author(s):  
Teruo Akiyama ◽  
Nobuo Miyamoto ◽  
Masami Oguro ◽  
Kenji Ogura
Keyword(s):  
Image Restoration ◽  
Document Image ◽  
Restoration Method

PDE-Based Image Processing

2012 ◽  
pp. 49-89
Author(s):  
Rajeev Srivastava
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Shape From Shading ◽  
Surface Geometry ◽  
Partial Differential ◽  
Basic Concepts ◽  
Processing Techniques ◽  
Image Modelling

This chapter describes the basic concepts of partial differential equations (PDEs) based image modelling and their applications to image restoration. The general basic concepts of partial differential equation (PDE)-based image modelling and processing techniques are discussed for image restoration problems. These techniques can also be used in the design and development of efficient tools for various image processing and vision related tasks such as restoration, enhancement, segmentation, registration, inpainting, shape from shading, 3D reconstruction of objects from multiple views, and many more. As a case study, the topic in consideration is oriented towards image restoration using PDEs formalism since image restoration is considered to be an important pre-processing task for 3D surface geometry, reconstruction, and many other applications. An image may be subjected to various types of noises during its acquisition leading to degraded quality of the image, and hence, the noise must be reduced. The noise may be additive or multiplicative in nature. Here, the PDE-based models for removal of both types of noises are discussed. As examples, some PDE-based schemes have been implemented and their comparative study with other existing techniques has also been presented.

Document image restoration using binary morphological filters

1996 ◽  
Author(s):  
Jisheng Liang ◽  
Robert M. Haralick ◽  
Ihsin T. Phillips
Keyword(s):  
Image Restoration ◽  
Document Image ◽  
Morphological Filters

scholarly journals Filtering and Wavelet Transform Algorithm for Old Document Image Restoration

2017 ◽  
Vol 8 (3) ◽  
pp. 177 ◽  
Author(s):  
Ridha Sefina Samosir
Keyword(s):  
Wavelet Transform ◽  
Data Collection ◽  
Image Restoration ◽  
Research Process ◽  
Document Image ◽  
Computer Based

The aim of this research was to develop image restoration system using filtering and wavelet transform algorithm. Data collection was through observation and system was developed using prototyping model. Result of this research is a computer based on system to restore image containing noise. Based on the research process, filtering and wavelet transform algorithm can used to restore old document image from interferences (noise).

PDE-Based Image Processing

2013 ◽  
pp. 569-607
Author(s):  
Rajeev Srivastava
Keyword(s):  
Image Processing ◽  
Image Restoration ◽  
Shape From Shading ◽  
Surface Geometry ◽  
Partial Differential ◽  
Basic Concepts ◽  
Processing Techniques ◽  
Image Modelling

This chapter describes the basic concepts of partial differential equations (PDEs) based image modelling and their applications to image restoration. The general basic concepts of partial differential equation (PDE)-based image modelling and processing techniques are discussed for image restoration problems. These techniques can also be used in the design and development of efficient tools for various image processing and vision related tasks such as restoration, enhancement, segmentation, registration, inpainting, shape from shading, 3D reconstruction of objects from multiple views, and many more. As a case study, the topic in consideration is oriented towards image restoration using PDEs formalism since image restoration is considered to be an important pre-processing task for 3D surface geometry, reconstruction, and many other applications. An image may be subjected to various types of noises during its acquisition leading to degraded quality of the image, and hence, the noise must be reduced. The noise may be additive or multiplicative in nature. Here, the PDE-based models for removal of both types of noises are discussed. As examples, some PDE-based schemes have been implemented and their comparative study with other existing techniques has also been presented.

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