The following options have a convolution kernel and a description of what the kernel does to a natural image. Select options that correctly describe the effect of the kernel on the image after convolution. (Note, vertical lines have changes in the horizontal direction. See @Madhav Malhotra's post in #questions on Slack for a visual example) || [100] 0 1 0; this would not change the image 0 0 1 0007 0 1 0; this would not change the image 000 [1 1 1] 1 1 1; this would not change the image 1 [1 1 1] 111; this would make the image smoother 1 10 20-2; this emphasize/detect horizontal changes in the image 10-1 0-17 20-2; this emphasize/detect vertical changes in the image 0 [1 2 1] 24 2; this would make the image smoother 1 2 1

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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The following options have a convolution kernel and a description of what the kernel does to a
natural image.
Select options that correctly describe the effect of the kernel on the image after convolution.
(Note, vertical lines have changes in the horizontal direction. See @Madhav Malhotra's post in
#questions on Slack for a visual example)
U
U
[100]
0 1 0; this would not change the image
001
го о
0
1
000
1
121
1
1
0
20
0
от
0; this would not change the image
-
1]
1; this would not change the image
1 1]
1; this would make the image smoother
-2 this emphasize/detect horizontal changes in the image
0 -1]
20 -2; this emphasize/detect vertical changes in the image
10-1
[1 2 1
2
4 2 ; this would make the image smoother
2 1
Transcribed Image Text:The following options have a convolution kernel and a description of what the kernel does to a natural image. Select options that correctly describe the effect of the kernel on the image after convolution. (Note, vertical lines have changes in the horizontal direction. See @Madhav Malhotra's post in #questions on Slack for a visual example) U U [100] 0 1 0; this would not change the image 001 го о 0 1 000 1 121 1 1 0 20 0 от 0; this would not change the image - 1] 1; this would not change the image 1 1] 1; this would make the image smoother -2 this emphasize/detect horizontal changes in the image 0 -1] 20 -2; this emphasize/detect vertical changes in the image 10-1 [1 2 1 2 4 2 ; this would make the image smoother 2 1
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Step 1

Introduction

Kernel:

A kernel, often referred to as a filter or a mask in the context of image processing, is a tiny matrix of integers that is applied to an image via the mathematical procedure known as convolution. The kernel is moved over the pixels in the image, and the values in the kernel are used to replace each pixel value with a weighted average of the nearby pixels. The kernel's function is to change the image in some way, such making it sharper or blurrier or emphasising particular details like the corners or edges. Kernels are a crucial tool in image processing and computer vision, and they are employed in a variety of tasks including object detection, segmentation, and image enhancement.

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