The gray histogram of digital image is described earlier, and the application of histogram is now tried. Histogram equalization
Histogram equalization (histogram equalization) is the most typical application of histogram, which is
Histogram equalizationHistogram equalization (histogram equalization) is the most typical application of histogram, which is a kind of image point operation . For an input image, an output image is generated by the operation, which means that the grayscale value of each pixel of the output image is determined by the input pixel point, i.e.:
Some header files:
#include
First, create a class:
Class histogram1d {PRIVATE: // number of points in the histogram int histsize [1]; // the histogram range is float hranges [2]; // pointer to this range const float * ranges [1]; // channel int channels [1]; public: // constructor histogram1d () {histsize [0] = 256; hranges [0] = 0.0; hranges [1] = 255.0; ranges [0] = hranges; channels [0] = 0 ;}
In open
Image processing-similar image recognition (histogram application) and image processing Histogram
Algorithm Overview:
First, histogram data is collected for the source image and the image to be filtered, and then the respective image histograms are normalized.
Calculate the histogram data using the babacache coefficien
[Translated from mos] explanation of histogram information and mos Article histogram Information
Interpreting histogram InformationSource:Interpreting Histogram Info (Doc ID 72539.1)
Applicable:Oracle Database-Enterprise Edition-Version 7.3.0.0 and laterOracle Database-Standard Edition-Version 7.3.0.0 and laterOracle
1 Grayscale Histogram
1.1 Concepts
Gray scale histogram is a function of gray level distribution, and it is the statistic of gray level distribution in image.
Grayscale histogram is the number of pixels in a digital image, according to the size of the gray value, the frequency of its occurrence. Gray-scale histogram i
Graphic histogram equalization and Python implementation, graphic histogram python
In the process of understanding the histogram equalization, I have referenced some books and blogs. What is confusing is that the author's understanding of the histogram remains on the surface and does not have a deep understanding of it
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First, histogram equalizationHistogram equalization is an important application of gray-scale transformation, it is widely used in image enhancement processing, it is based on the cumulative distribution function transformation of the histogram correction method, can produce a gray scale distribution with uniform probability density of the image, expand the value dynamic range of the pixel. The gray value o
Histogram equalization (histogram equalization)The "central idea" of histogram equalization is to change the gray histogram of the original image from a certain gray area in the comparative concentration to the uniform distribution in the whole gray range. Histogram equaliza
In the C programming language (version 2nd), there is an exercise that prints a horizontal or vertical histogram of the number of words, see page 17th. Now suppose we've got a count array of words.The horizontal histogram is simple to print, only two loops are required, and the number of times the outer loop executes is the array length. The inner loop is the size of each element of the array. Here's how:1/
Oracle histogram, Histogram
Histogram when the data distribution of a column is uneven, in order to allow CBO to generate the best execution plan, we may need to collect a histogram for the table. The maximum number of buckets in the histogram is 254. It is a very time-consu
Similar image search principle 3 (color histogram-c ++), image search Histogram
The color histogram of an image can be used for image retrieval. It can be used for image retrieval with the same color and with translation, scaling, and rotation immutability. Of course, these three features are not as stable as sift or surf, in addition, the biggest limitation is t
PHP implementation Dynamic histogram improved version, PHP histogram improved version
In this paper, an improved version of dynamic histogram for PHP is analyzed. Share to everyone for your reference. The specific analysis is as follows:
It has been written that if only the dynamic histogram of the case, the principle
Histogram of oriented gridients, abbreviated as HOG, is one of the most common features of image local texture in computer vision and Pattern recognition field. This characteristic name is also very straightforward, that is, to calculate the image of a region in different directions of the gradient values, and then accumulate, get the histogram, this histogram, i
Itzik Ben-Gan
Similarly, with histograms, you can analyze the sampling of performance counters (such as CPU utilization and memory) set on the server in the network. For example, assume that you record the CPU usage of a network server every five minutes, and the value measured on a certain day changes between 21% and 100%. You can generate a histogram with four levels-20 to 40, 40 to 60, 60 to 80, and 80 to 100-to obtain the number of samples of each
Given n non-negative integers representing the histogram ' s bar height where the width of each bar is 1, find the Area of largest rectangle in the histogram.Above is a histogram the where width of each bar is 1, given height = [2,1,5,6,2,3] .The largest rectangle is shown in the shaded area, and which has an area = 10 unit.For example,Given height = [2,1,5,6,2,3] ,Return 10 .Train of thought: This problem
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This is an algorithm problem on Leetcode, the following is my idea of solving this problem and the application of this problem. Topics
Largest rectangular area in a histogram
Given n non-negative integers representing the histogram's bar height where the width of each bar are 1, find the area of L Argest rectangle in the histogram.
Above is a
6. Counting vertical histogram output and counting vertical histogram output
1 # include
It is a headache to do this exercise at the beginning, because the histogram is drawn in the vertical direction, it must be a column from left to right.
But now the output logic is from top to bottom, conflicting. After reading the normative answers, I don't know how to sta
Given n non-negative integers representing the histogram ' s bar height where the width of each bar is 1, find the Area of largest rectangle in the histogram.Above is a histogram the where width of each bar is 1, given height = [2,1,5,6,2,3] .The largest rectangle is shown in the shaded area, and which has an area = 10 unit.For example,Given height = [2,1,5,6,2,3] ,Return 10 .This problem let straight squar
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