In MATLAB, a grey-scale image is stored a a matrix of numbers, all between 0 (black) and 255 (white). Since there are 256 possible values, 8 bits are needed or each pixel, in contrast to a normal integer, which is 64 bits.To save memory, grey-scale images are stored with a special data type, uint8 (unsigned 8-bit integer). In computer terminology, 8 bits = 1 byte. Even at one byte per pixel, a large image can consume a lot of memory. For example, a 1000x1000-pixel image takes 1 million bytes (which is a little less than 1 megabyte, since by convention 1 Mbyte = 2^20 bytes). One technique for reducing the size of an image is quantization - reducing the number of allowable levels from 256 to something smaller. Surprisingly, most images can be quantized by a large factor without losing much information. In this problem, you will quantize a grey-scale image to only 4 levels, so that it could (in principle) be stored as 2 bits per pixel. The template will read in an image file. Your job is to loop over all rows and columns of the image matrix, N, and set each pixel to 0, 1, 2, or 3 as follows: original pixel value new pixel value 0 - 64 0 65 - 128 1 129 - 192 2 193 - 255 3 Use imshow to display the original and modified images so that you can see the effect of the quantization.
In MATLAB, a grey-scale image is stored a a matrix of numbers, all between 0 (black) and 255 (white). Since there are 256 possible values, 8 bits are needed or each pixel, in contrast to a normal integer, which is 64 bits.To save memory, grey-scale images are stored with a special data type, uint8 (unsigned 8-bit integer). In computer terminology, 8 bits = 1 byte. Even at one byte per pixel, a large image can consume a lot of memory. For example, a 1000x1000-pixel image takes 1 million bytes (which is a little less than 1 megabyte, since by convention 1 Mbyte = 2^20 bytes). One technique for reducing the size of an image is quantization - reducing the number of allowable levels from 256 to something smaller. Surprisingly, most images can be quantized by a large factor without losing much information. In this problem, you will quantize a grey-scale image to only 4 levels, so that it could (in principle) be stored as 2 bits per pixel. The template will read in an image file. Your job is to loop over all rows and columns of the image matrix, N, and set each pixel to 0, 1, 2, or 3 as follows: original pixel value new pixel value 0 - 64 0 65 - 128 1 129 - 192 2 193 - 255 3 Use imshow to display the original and modified images so that you can see the effect of the quantization.
Chapter3: Data Representation
Section: Chapter Questions
Problem 7RQ
Related questions
Topic Video
Question
In MATLAB, a grey-scale image is stored a a matrix of numbers, all between 0 (black) and 255 (white). Since there are 256 possible values, 8 bits are needed or each pixel, in contrast to a normal integer, which is 64 bits.To save memory, grey-scale images are stored with a special data type, uint8 (unsigned 8-bit integer). In computer terminology, 8 bits = 1 byte.
Even at one byte per pixel, a large image can consume a lot of memory. For example, a 1000x1000-pixel image takes 1 million bytes (which is a little less than 1 megabyte, since by convention 1 Mbyte = 2^20 bytes).
One technique for reducing the size of an image is quantization - reducing the number of allowable levels from 256 to something smaller. Surprisingly, most images can be quantized by a large factor without losing much information. In this problem, you will quantize a grey-scale image to only 4 levels, so that it could (in principle) be stored as 2 bits per pixel.
The template will read in an image file. Your job is to loop over all rows and columns of the image matrix, N, and set each pixel to 0, 1, 2, or 3 as follows:
original pixel value new pixel value
0 - 64 0
65 - 128 1
129 - 192 2
193 - 255 3
Use imshow to display the original and modified images so that you can see the effect of the quantization.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
This is a popular solution!
Trending now
This is a popular solution!
Step by step
Solved in 3 steps
Knowledge Booster
Learn more about
Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, computer-science and related others by exploring similar questions and additional content below.Recommended textbooks for you
Systems Architecture
Computer Science
ISBN:
9781305080195
Author:
Stephen D. Burd
Publisher:
Cengage Learning
Systems Architecture
Computer Science
ISBN:
9781305080195
Author:
Stephen D. Burd
Publisher:
Cengage Learning