Algorithm to compute Basis images of an image

In summary, the conversation discusses the representation of signals and images as a summation of elementary signals or basis images. The person is looking for available code or an algorithm to compute the basis images of an image. Suggestions are given to search for libraries and source code in MPEG and JPEG, and to look into SVD decomposition for pertinent orthogonal basis. The person also shares their MATLAB code for computing magnitude and phase spectrum, and asks for clarification on what information is being sought.
  • #1
ramdas
79
0
I know from the Fourier Analysis
that any signal can be represented
as summation of elementary
signals i.e. basis functions
.Likewise,any image can be
represented as summation of Basis images.

Is there any available code, or
even an algorithm, that would
allow me to compute Basis images
of an image?
 
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  • #2
Hey ramdas.

I think you should search for MPEG and JPEG code libraries and look at the source code for an open source project.

That should give you a good lot of code to start off with.
 
  • #3
You have basis image from fourrier analysis and basis image from other function decomposition. Good basis images used in Computer vision are the eigen vector of the image. You can find explanation by looking to SVD, SVD compression, SVD image decomposition. This method give pertinent ortogonal basis to explain images.
 
  • #4
@kroni ,@chiro Sir ,I have done basic programming in MATLAB. I have computed magnitude and phase spectrum using "fft2 "function in MATLAB.I am adding my code .But i don't know how to move forward
Code:
clc;
clear all;
close all;

i=imread('C:\Users\RK\Desktop\cameraman.gif');
%i=rgb2gray(i);
i=uint8(i);

figure,
subplot(1,3,1);imshow(i);
%title('\alpha^2 and X_1')
%title('\ite^-1000*|t|');
%title('e^{-1000|t|}');
title('\ite^{-1000 |t|}','Color','b')
%title('Cameraman Gray scale Image');

f1=fft2(i);
f2=log(1+fftshift(f1));

m=abs(f2);
subplot(1,3,2);
imshow(m,[]);
title('Magnitude Spectrum');

phase=angle(f2);
subplot(1,3,3);
imshow(phase,[]);
title('Phase Spectrum');
 
  • #5
what do you want to obtain ?
 
  • #6
I think he is trying to get the frequency information of a two-dimensional signal (since I noticed ff2 function there).

If you want to get the gray-scale information you should either do an average function of the RGB values or use a transform like they do in NTSC images.

Also try and plot the image based on re-constructing the signal with a specific bandwidth by creating a bitmap file and passing it to MATLAB for rendering.
 

Related to Algorithm to compute Basis images of an image

1. What is an algorithm to compute basis images of an image?

An algorithm to compute basis images of an image is a set of instructions that can be followed to determine the basis images, also known as the fundamental images, of a given image. These basis images are the building blocks that make up the original image and can be used to reconstruct it.

2. How does an algorithm compute basis images of an image?

An algorithm computes basis images of an image by first converting the image into a matrix of pixels. It then uses mathematical operations, such as matrix decomposition, to identify the fundamental images. The algorithm then calculates the coefficients for each basis image, which represent the importance of that image in the overall composition of the original image.

3. What are the benefits of using an algorithm to compute basis images of an image?

One of the main benefits of using an algorithm to compute basis images is that it allows for a more efficient way of storing and transmitting images. By representing an image as a combination of basis images, the overall file size can be reduced. Additionally, this method allows for easier manipulation and editing of images.

4. Can an algorithm accurately compute basis images of any type of image?

Yes, an algorithm can accurately compute basis images of any type of image, as long as the image is in a digital format and can be represented as a matrix of pixels. However, the accuracy of the basis images will depend on the complexity and quality of the original image, as well as the efficacy of the algorithm being used.

5. How can I use basis images generated by an algorithm?

Basis images can be used for a variety of purposes, such as image compression, image editing, and image recognition. By manipulating the coefficients of the basis images, an image can be altered or enhanced in specific ways. Basis images can also be used in machine learning algorithms for tasks such as image classification and object detection.

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