# Color detection in matlab

The following Matlab project contains the source code and Matlab examples used for color detection.
RGB color detection in images and Real time video is presented in this project.

The following Matlab project contains the source code and Matlab examples used for this function encoded a text file in an image. .
The following programs hide a text file in an image of 256 colours encrypted disordering the characters and transforming it then into a group of pixels of colours.

The following Matlab project contains the source code and Matlab examples used for jpeg image encryption using fuzzy pn sequences.
This software release consists of an implementation of the algorithm described in the paper:
B.

The following Matlab project contains the source code and Matlab examples used for gui layout toolbox.
This toolbox provides tools to create sophisticated MATLAB graphical user interfaces that resize gracefully.

The following Matlab project contains the source code and Matlab examples used for firquest optimizes the quantization of fir coefficients. .
FIRQUEST searches for a quantized filter with optimal stopband rejection, using an unquantized filter as a starting point.

The following Matlab project contains the source code and Matlab examples used for encipher image into text.
"Is it possible to save an image as a text file and then reproduce the image from the RGB values (reading in the order from left to right and top to bottom) using an image reader?
I am thinking of producing a camera that saves text files instead of jpgs.

The following Matlab project contains the source code and Matlab examples used for broken strand detection.
A visual method for OGW broken strand detection.

The following Matlab project contains the source code and Matlab examples used for 3d spiht.
These functions implement the 3D SPIHT algorithm, used for the compression of 3d wavelet coefficients. Such 3d wavelet coefficients are produced during the coding of video sequences.

The following Matlab project contains the source code and Matlab examples used for miscellaneous tools for image processing.
eachchannel
allows us to apply function for each channel
imgrad
calculates horizontal and vertical gradients
impsnr
evaluates the psnr and the rmse beween images
imreadind
reads image file from file even if the image file is index color, imreadind can read image data as well as rgb image data
rgb2ycc
transfers color space from rgb to ycc
ycc2rgb
transfers color space from ycc to rgb
.

The following Matlab project contains the source code and Matlab examples used for peak signal to noise ratio.
function [A] = psnr(image,image_prime,M,N)
comparison between "image" and "image_prime"
"M , N" size of "image" (the two images must be of the same size)
The typical values of PSNR for images of good quality vary between 30 and 40 dB.

The following Matlab project contains the source code and Matlab examples used for signal to noise ratio .
The MSE calculated by averaging the squared intensity differences of distorted and reference image pixels, along with the related quantity of PSNR,

The following Matlab project contains the source code and Matlab examples used for a simple function to find psnr between two images! .
This function PSNR = calcpsnr(f,F), will compute the PSNR of two given images.

The following Matlab project contains the source code and Matlab examples used for peak signal to noise ratio (psnr).
Calculates the Peak Signal-to-Noise Ratio given an input and an output color
image of 8-bit colour.
RGB is converted to YCbCr colour space before proper arithmetic
operations and the luma channel is used for PSNR computation.

The following Matlab project contains the source code and Matlab examples used for psnr, peak signal to noise ratio.
% PSN is PSNR of Image Peak signal to noise ratio.

The following Matlab project contains the source code and Matlab examples used for bjontegaard metric calculation (bd psnr).
Fixed script for Bjontegaard metric calculation. Original script has wrong integration interval.

The following Matlab project contains the source code and Matlab examples used for measurment psnr and snr and mse.
this function is used to compare between to matices or arrays of data

The following Matlab project contains the source code and Matlab examples used for psnr (image processing).
Calculates the Peak-to-peak signal to noise ratio of two images X and Y.

The following Matlab project contains the source code and Matlab examples used for psnr for rgb images.
The function, PSNR_RGB( X,Y) computes the PSNR for two RGB images using the formula :
MSE(X,Y)=SUM(1,n)SUM(1,m)SUM(1,p) [X(i,j,k)-Y(i,j,k)]²
d= max(max(X),max(Y))|
PSNR(X,Y)=10.

The following Matlab project contains the source code and Matlab examples used for psnr for 2d images.
Just double click on input panel to PSNR
and browse the two images for which you want to calculate the PSNR.

The following Matlab project contains the source code and Matlab examples used for psnr of yuv videos.
The function computes the psnr between two yuv videos.

The following Matlab project contains the source code and Matlab examples used for psnr of image.
Peak signal-to-noise ratio, often abbreviated PSNR, is an engineering term for the ratio between the maximum possible power of a signal and the power of corrupting noise that affects the fidelity of its representation.

The following Matlab project contains the source code and Matlab examples used for psnr calculator.
A simple PSNR calculator that might be handy in measuring the PSNR between two frames in a video. Typically used in measuring the distortion when videos are encoded and decoded.

The following Matlab project contains the source code and Matlab examples used for peak signal to noise ratio .
The MSE calculated by averaging the squared intensity differences of distorted and reference image pixels, along with the related quantity of PSNR,

The following Matlab project contains the source code and Matlab examples used for this function displays the psnr (peak signal-to-noise ratio) between two images. .
This function displays the PSNR (peak signal-to-noise ratio) between two images.

A discrete cosine transform (DCT) expresses a finite sequence of data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering, from lossy compression of audio (e.g. MP3) and images (e.g. JPEG) (where small high-frequency components can be discarded), to spectral methods for the numerical solution of partial differential equations.

The following Matlab project contains the source code and Matlab examples used for discrete cosine transform based image fusion techniques.
Image fusion using DCT based demo programme is presented.

The following Matlab project contains the source code and Matlab examples used for multi focus image fusion for visual sensor networks in dct domain.
Attached is the simulation of following multifocus image fusion methods:
(1) DCT+Variance
(2) DCT+Variance+CV
proposed in:
M.

The following Matlab project contains the source code and Matlab examples used for novel image fusion techniques using dct.
DCT based image are presented with 1D DCT and 2D DCT for image fusion.

The following Matlab project contains the source code and Matlab examples used for multi focus image fusion in dct domain.
Attached is the simulation of following multi-focus image fusion methods:
(1) DCT+Variance
(2) DCT+Variance+CV
proposed in:
M.

The following Matlab project contains the source code and Matlab examples used for directional discrete cosine transform.
DDCT is demonstrated with different block size and different modes. The details algorithm can be referred at
http://link.springer.com/article/10.1007/s12596-013-0148-7?no-access=true
VPS Naidu "Hybrid DDCT-PCA based multi sensor image fusionJournal of Optics", Volume 43, Issue 1, pp 48-61, March 2014,