# Histogram

# Pairwise joint bivariate histograms for many variables in matlab

# Logicle histogram in matlab

# Entropy estimation from histogram in matlab

# 3d histogram of rgb image in matlab

# Finding histogram of an image in matlab

# Price volume chart in matlab

# Function to make a 2d histogram in matlab

# Search duplicate images in sub folders using histogram in matlab

# 3d imaq waterfall in matlab

# Histogram 2d in matlab

# Fast mutual information, joint entropy, and joint histogram calculation for n d images in matlab

# Color histogram of an rgb image in matlab

# Statistical analysis in matlab

# Reversible image data hiding using quad tree segmentation and histogram shifting in matlab

# Radialdistribution2d in matlab

# Diagonal histogram of non zero elements in matlab

# Histogram fitting probability density, counts, frequency in matlab

# Simply show a histogram of distances between geographic waypoints. in matlab

# General framework to histogram shifting based reversible data hiding in matlab

# Normalized histogram in matlab

# Fuzzy color histogram in matlab

# Hog Matlab Code

Histogram of Oriented Gradients (HOG) are feature descriptors used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized portions of an image. This method is similar to that of edge orientation histograms, scale-invariant feature transform descriptors, and shape contexts, but differs in that it is computed on a dense grid of uniformly spaced cells and uses overlapping local contrast normalization for improved accuracy.

# Histogram of oriented gradients (hog) code using matlab

# Hog (histogram of oriented gradients) mex implementation in matlab

# Histogram binwidth optimization in matlab

# Gpu accelerated edge region based level set evolution constrained by 2d gray scale histogram in matlab

# Histogram based class separability measure in matlab

# Toolbox fast marching in matlab

# Histogram Matching Matlab Code

Histogram matching is a method in image processing of color adjustment of two images using the image histograms.

It is possible to use histogram matching to balance detector responses as a relative detector calibration technique. It can be used to normalize two images, when the images were acquired at the same local illumination (such as shadows) over the same location, but by different sensors, atmospheric conditions or global illumination.