RIZVI EDUCATION SOCIETYS RIZVI COLLEGE OF ENGINEERING DEPARTMENT
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RIZVI EDUCATION SOCIETY’S RIZVI COLLEGE OF ENGINEERING DEPARTMENT: ELECTRONICS &TELECOMMUNICATIONS Class: T. E. Semester: VI Course Name: Image Processing & Machine Vision Course Code: ECC 604 Module No. : 2 Topic: Image Enhancement In Spatial Domain (Neighborhood Processing) Prepared by: Prof. Sudesh Agrawal
Rizvi College of Engineering CONTENTS Spatial Filtering Low Pass Filtering High Pass Filtering Image Processing & Machine Vision Prof. Sudesh Agrawal
Rizvi College of Engineering SPATIAL FILTERING Spatial Filtering is an extension of point processing techniques to enhance an image. In this filtering technique, instead of working on an individual pixel, a group of pixels are taken and then multiplied with a mask. The behavior of this mask decides the nature of output image. A low pass mask will provide a low frequency filtered image and vice versa in case of high pass mask. Image Processing & Machine Vision Prof. Sudesh Agrawal
Rizvi College of Engineering Image Processing & Machine Vision Prof. Sudesh Agrawal
Rizvi College of Engineering PERFORMING SPATIAL FILTERING Image Processing & Machine Vision Prof. Sudesh Agrawal
Rizvi College of Engineering LOW PASS FILTERING A low pass mask can be of 3 x 3, 5 x 5, 7 x 7, etc. Following is the 3 x 3 averaging low pass mask: Image Processing & Machine Vision 1/9 1/9 1/9 Prof. Sudesh Agrawal
Rizvi College of Engineering High Frequency Edge Normalized Edge Post Filtering 10 10 10 10 10 180 180 180 180 180 10 10 10 66. 6 123. 3 180 180 180 Image Processing & Machine Vision Prof. Sudesh Agrawal
Rizvi College of Engineering LOW PASS FILTERED OUTPUT Image Processing & Machine Vision Prof. Sudesh Agrawal
Rizvi College of Engineering HIGH PASS FILTERING A high pass mask can be of 3 x 3, 5 x 5, 7 x 7, etc. Following is the 3 x 3 averaging low pass mask: Image Processing & Machine Vision -1/8 1 -1/8 Prof. Sudesh Agrawal
Rizvi College of Engineering High Frequency Edge Retention Post Filtering 10 10 10 10 10 180 180 180 180 180 0 0 0 0 109 109 109 0 0 0 Image Processing & Machine Vision ! Negative Pixels are to be made zero, since zero in IP means black color. A negative pixel would mean a color which is blacker than black, meaning black! Prof. Sudesh Agrawal
Rizvi College of Engineering HIGH PASS FILTERED OUTPUT Image Processing & Machine Vision Prof. Sudesh Agrawal
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