CN111563865A - Image detail enhancement method and device for brightness preservation of consumer electronic products - Google Patents

Abstract

The invention provides an image detail enhancement method and device for maintaining brightness of a consumer electronic product, which are characterized in that on the basis of an image histogram, the histogram of an input image is automatically divided into a plurality of block histograms according to the characteristics of the input image, histogram equalization calculation is carried out in each block, and finally an enhanced image is merged and output, so that the contrast and detail presenting capability of the output image are improved under the condition that the brightness of the input image and the brightness of the output image are basically consistent according to the requirements of the consumer electronic product and an infrared image processing image, the brightness of the input image can be well maintained, the contrast enhancement of the image can be realized, and the image detail can be clearly presented.

Description

Image detail enhancement method and device for brightness preservation of consumer electronic products

technical field

The invention relates to the technical field of image contrast enhancement, and in particular, to a method and device for enhancing image details for maintaining brightness of consumer electronic products.

Background technique

Global histogram equalization is one of the commonly used methods for digital image enhancement. Although its algorithm is simple to implement, it is not suitable for implementation in consumer electronic products such as televisions, digital cameras, and video cameras. This is because the traditional global histogram equalization algorithm (HE) cannot maintain the brightness of the input and output images well, that is, the brightness of the output image processed by the HE algorithm will have a large deviation from the brightness of the input image. Therefore, for some consumer electronic products and infrared image processing systems (which require the output image to maintain the brightness of the input image), the HE algorithm often cannot obtain a satisfactory output image.

To be able to solve this problem efficiently, many HE-based algorithms have been proposed. Although some methods can enhance the overall contrast of the image and keep the brightness better, they often cannot achieve effective enhancement of local details, resulting in unsatisfactory output images.

SUMMARY OF THE INVENTION

The present invention aims to provide an image detail enhancement method and apparatus for maintaining brightness of a consumer electronic product that overcomes one of the above problems or at least partially solves any of the above problems.

In order to achieve the above object, the technical scheme of the present invention is specifically realized in this way:

累积概率

其中i＝1...length(Hx)；对第一公共数组Hx中各分块直方图按如下公式计算：

其中i＝1...length(Hx)，f(i)为输出图像的灰度值，P₁为图像细节、亮度、对比度的调节参数；输出输出图像imageout。One aspect of the present invention provides an image detail enhancement method for brightness preservation of consumer electronic products, comprising: calculating a grayscale histogram h(i) and a probability p(i) of a grayscale input image I, where i is Gray level, set the output image imageout to be the same size as the input image I, and set the value to a zero matrix; use the first array h ₁ to record the histogram that conforms to the first rule, and use the first gray level array id ₁ to record the corresponding gray level , use the second array h ₂ to record the histogram conforming to the second rule, and use the second gray level array id ₂ to record the corresponding gray level, wherein the first rule includes 0<p(i)<=1/255, the first The second rule includes: p(i)>1/255; subdivide the first array h ₁ and the second array h ₂ , and use the jgh ₁ array to record the difference between two adjacent numbers in the first grayscale array id ₁ , Use the jg ₁ array to record the value of jgh ₁ (x)>=preset value, the size of the divided blocks is 1+length(jg ₁ ); use the jgh ₂ array to record the second grayscale array id ₂ The two adjacent numbers Poor, use the jg ₂ array to record the value of jgh ₂ (x)>= preset value, the number of divided blocks is 1+length (jg ₂ ); set the first public array Hx to store the block histogram, and the second public array idx Stores the gray level of the first public array Hx, wherein the acquisition method of each block histogram Hx in the first array h ₁ is: judging whether the jg ₁ array is empty, if it is empty, determine that the first array h ₁ cannot be divided , then let the first public array Hx=h ₁ , the second public array idx=id ₁ , the length of the block histogram stored in the first public array Hx is length(Hx); if not empty, determine the first array h ₁ It can be divided again, the number of divided blocks is 1+length(jg ₁ ), and the histogram of any block in 1...(1+length(jg ₁ )) is Hx=h ₁ (T1:jg ₁ (i )), the gray level of the corresponding block histogram is idx=id ₁ (T1:jg ₁ (i)), where i=1...n ₁ -1, when i=1, T1=1, at When i=2...n ₁ -1, T1=1+jg ₁ (i); the acquisition method of each block histogram Hx in the second array h ₂ is: judging whether the jg ₂ array is empty, if it is empty , determine that the second array h ₂ cannot be divided, then let the first public array Hx=h ₂ , the second public array idx=id ₂ , and the length of the block histogram stored in the first public array Hx is length(Hx); If it is empty, it is determined that the second array h ₂ can be divided again, the number of divided blocks is 1+length(jg ₂ ), and the histogram of any block in 1...(1+length(jg ₂ )) is Hx= h ₂ (T2:jg ₂ (i)), the gray level of the corresponding block histogram is idx=id ₂ (T 2: jg ₂ (i)) where i=1...n ₂ -1, when i=1, T2=1, when i=2...n ₂ -1, T2=1+jg ₂ (i); Calculate the probability of each block histogram in the first public array Hx

cumulative probability

where i=1...length(Hx); the histogram of each block in the first public array Hx is calculated according to the following formula:

where i=1...length(Hx), f(i) is the gray value of the output image, P ₁ is the adjustment parameter of image detail, brightness and contrast; output the output image imageout.

Among them, the value range of P ₁ is [0,1].

Wherein, P ₁ =0.1.

Among them, the default value is 20.

累积概率

其中i＝1...length(Hx)；第三计算模块，用于对第一公共数组Hx中各分块直方图按如下公式计算：Another aspect of the present invention provides a brightness-preserving image detail enhancement device for consumer electronic products, comprising: a first calculation module for calculating a gray-level histogram h(i) and a probability p of a gray-scale input image I (i), wherein, i is the gray level, the output image imageout is set to be the same size as the input image I, and the numerical value is set to a zero matrix; the recording module is used to record the histogram that conforms to the first rule by using the first array h ₁ , using The first gray level array id ₁ records the corresponding gray level, the second array h ₂ is used to record the histogram conforming to the second rule, and the second gray level array id ₂ is used to record the corresponding gray level, wherein the first rule includes 0<p(i)<=1/255, the second rule includes: p(i)>1/255; the division module is used to subdivide the first array h ₁ and the second array h ₂ , using jgh ₁ The array records the difference between two adjacent numbers in the first grayscale array id ₁ , and uses the jg ₁ array to record the value of jgh ₁ (x)>=preset value, and the number of divided blocks is 1+length(jg ₁ ); using The jgh ₂ array records the difference between two adjacent numbers in the second grayscale array id ₂ , and uses the jg ₂ array to record the value of jgh ₂ (x)>=preset value, and the number of divided blocks is 1+length(jg ₂ ) Determine the module, for setting the first public array Hx to store the block histogram, the second public array idx to store the gray level of the first public array Hx, wherein, the acquisition of each block histogram Hx in the first array h ₁ The method is: judging whether the jg ₁ array is empty, if it is empty, it is determined that the first array h ₁ cannot be divided, then the first public array Hx=h ₁ , the second public array idx=id ₁ , and the first public array Hx is stored The length of the block histogram is length(Hx); if it is not empty, it is determined that the first array h ₁ can be divided again, and the number of divided blocks is 1+length(jg ₁ ), for 1...(1+length (jg ₁ )), the arbitrary block histogram is Hx=h ₁ (T1:jg ₁ (i)), and the gray level of the corresponding block histogram is idx=id ₁ (T1:jg ₁ (i)), where i=1...n ₁ -1, when i=1, T1=1, when i=2...n ₁ -1, T1=1+jg ₁ (i); the second array h ₂ The acquisition method of each block histogram Hx is as follows: judging whether the jg ₂ array is empty, if it is empty, it is determined that the second array h ₂ cannot be divided, then the first public array Hx=h ₂ , the second public array idx= id ₂ , the length of the block histogram stored in the first public array Hx is length(Hx); if it is not empty, it is determined that the second array h ₂ can be divided again, and the number of divided blocks is 1+length(jg ₂ ), For any block histogram in 1...(1+length(jg ₂ )), Hx=h ₂ (T2:jg ₂ (i)), the gray level of the corresponding block histogram is idx=id ₂ (T2:jg ₂ (i)), where i=1...n ₂ -1, when i=1, T2= 1. When i=2...n ₂ -1, T2=1+jg ₂ (i); the second calculation module is used to calculate the probability of each block histogram in the first public array Hx

cumulative probability

Wherein i=1...length(Hx); the third calculation module is used to calculate the histogram of each block in the first public array Hx according to the following formula:

其中i＝1...length(Hx)，f(i)为输出图像的灰度值，P₁为图像细节、亮度、对比度的调节参数；输出模块，用于输出输出图像imageout。

where i=1...length(Hx), f(i) is the gray value of the output image, P ₁ is the adjustment parameter of image detail, brightness and contrast; the output module is used to output the output image imageout.

Among them, the value range of P ₁ is [0,1].

Wherein, P ₁ =0.1.

Among them, the default value is 20.

It can be seen that, the method and device for enhancing image details for maintaining the brightness of consumer electronic products provided by the embodiments of the present invention are based on the image histogram, and automatically divide the histogram of the input image into several block histograms according to the characteristics of the input image. image, and perform histogram equalization calculation in each block, and finally combine and output the enhanced image, so that the contrast of the output image can be improved under the condition that the brightness of the input and output images are basically the same for consumer electronic products and infrared image processing images. With the ability to present details, it can better maintain the brightness of the input image, and at the same time, it can enhance the contrast of the image and present the details of the image clearly.

Description of drawings

In order to illustrate the technical solutions of the embodiments of the present invention more clearly, the following briefly introduces the accompanying drawings used in the description of the embodiments. The drawings in the following description are only some For those of ordinary skill, other drawings can be obtained from these drawings without any creative effort.

FIG. 1 is a flowchart of a method for enhancing image details for maintaining brightness of a consumer electronic product according to an embodiment of the present invention;

2 is a schematic structural diagram of an image detail enhancement device for maintaining brightness of a consumer electronic product according to an embodiment of the present invention;

3 is a schematic diagram of a general brightness image-flower pot provided by an embodiment of the present invention;

4 is a low-brightness image-landscape schematic diagram provided by an embodiment of the present invention;

5 is a schematic diagram of an infrared image provided by an embodiment of the present invention;

FIG. 6 is a schematic diagram of a high-brightness image—a plum blossom provided by an embodiment of the present invention.

Detailed ways

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be more thoroughly understood, and will fully convey the scope of the present disclosure to those skilled in the art.

FIG. 1 shows a flowchart of a method for enhancing image details for maintaining brightness of a consumer electronic product provided by an embodiment of the present invention. Referring to FIG. 1 , the method for enhancing image details for maintaining brightness for a consumer electronic product provided by an embodiment of the present invention, include:

S1, calculate the grayscale histogram h(i) and probability p(i) of the grayscale input image I, where i is the grayscale level, set the output image imageout to be the same size as the input image I, and set the value to a zero matrix.

输出图像imageout的图像大小可以与输入图像I的矩阵相同，例如输入图像I的矩阵是20×11，输出图像imageout也是20×11，输出图像imageout的数据表中的数据为0。Specifically, the gray level histogram h(i) and the probability p(i) of the input image I can be calculated by using the existing formula. where: probability

The image size of the output image imageout can be the same as the matrix of the input image I. For example, the matrix of the input image I is 20×11, the output image imageout is also 20×11, and the data in the data table of the output image imageout is 0.

S2, use the first array h ₁ to record the histogram conforming to the first rule, use the first gray level array id ₁ to record the corresponding gray level, use the second array h ₂ to record the histogram conforming to the second rule, use the second The gray level array id ₂ records the corresponding gray level, wherein the first rule includes 0<p(i)<=1/255, and the second rule includes: p(i)>1/255.

Specifically, the histogram of 0<p(i)<=1/255 is divided into one class and recorded by h ₁ array, that is, h ₁ (1)...h ₁ (n ₁ ) records the statistics, id ₁ (1 )...id ₁ (n ₁ ) means that the id ₁ array records the corresponding gray level; in the same way, the histogram of p(i)>1/255 is divided into another type and recorded by the h ₂ array, that is, h ₂ (1) ...h ₂ (n ₂ ) records the statistics, id ₂ (1)...id ₂ (n ₂ ) means that the id ₂ array records the corresponding gray level. Wherein, n ₁ is the number of histograms in the first array h ₁ , and n ₂ is the number of histograms in the second array h ₂ .

S3, subdivide the first array h ₁ and the second array h ₂ , use the jgh ₁ array to record the difference between two adjacent numbers in the first grayscale array id ₁ , and use the jg ₁ array to record jgh ₁ (x)> = The value of the preset value, the number of divided blocks is 1+length(jg ₁ ); the jgh ₂ array is used to record the difference between two adjacent numbers in the second grayscale array id ₂ , and the jg ₂ array is used to record jgh ₂ (x )>=the value of the preset value, the number of divided blocks is 1+length(jg ₂ ).

As an optional implementation manner of the embodiment of the present invention, the preset value is 20. Specifically, in this step, the histograms h ₁ and h ₂ are re-segmented. Using the formula jgh ₁ (x)=id ₁ (x+1)-id ₁ (x)x=1...n ₁ -1, record the difference between two adjacent numbers in the id ₁ array, and put the difference in the jgh ₁ array , at the same time, the value of jgh ₁ (x)>=20 is placed in the array jg ₁ , and the number of divided blocks is 1+length(jg ₁ ); similarly, using the formula jgh ₂ (x)=id ₂ (x+1) -id ₂ (x)x=1...n ₂ -1, record the difference between two adjacent numbers in the id ₂ array, put the difference in the jgh ₂ array, and put the value of jgh ₂ (x)>=20 in the array In jg ₂ , the number of divided blocks is 1+length(jg ₂ ).

S4, set the first public array Hx to store the block histogram, and the second public array idx to store the gray level of the first public array Hx, wherein, the acquisition method of each block histogram Hx in the first array h ₁ is: judging Whether the jg ₁ array is empty, if it is empty, it is determined that the first array h ₁ cannot be divided, then let the first public array Hx=h ₁ , the second public array idx=id ₁ , and the block histogram stored in the first public array Hx The length of the graph is length(Hx); if it is not empty, it is determined that the first array h ₁ can be divided again, and the number of divided blocks is 1+length(jg ₁ ), for 1...(1+length(jg ₁ ) ) in any block histogram is Hx=h ₁ (T1:jg ₁ (i)), and the gray level of the corresponding block histogram is idx=id ₁ (T1:jg ₁ (i)), where i=1 ...n ₁ -1, when i=1, T1=1, when i=2...n ₁ -1, T1=1+jg ₁ (i); each block in the second array h ₂ The acquisition method of the histogram Hx is as follows: judging whether the jg ₂ array is empty, if it is empty, it is determined that the second array h ₂ cannot be divided, then the first public array Hx=h ₂ , the second public array idx=id ₂ , the The length of the block histogram stored in a public array Hx is length(Hx); if it is not empty, it is determined that the second array h ₂ can be divided again, and the number of divided blocks is 1+length(jg ₂ ), for 1.. .(1+length(jg ₂ )), the arbitrary block histogram is Hx=h ₂ (T2:jg ₂ (i)), and the gray level of the corresponding block histogram is idx=id ₂ (T2:jg ₂ (i)), where i= ₁ ...n2-1, when i=1, T2=1, and when i= ₂ ...n2-1, T2=1+ _jg2 (i).

Specifically, the public array Hx is set to store the block histogram, the public array idx is set to store the gray level of Hx, and the acquisition method of each block histogram Hx in the histogram _h1 is: _first , determine whether the array jg1 is empty (isempty (jg ₁ )==1), if it is empty, it indicates that the histogram h ₁ cannot be divided, then Hx=h ₁ , idx=id ₁ , the length of the segment Hx is length(Hx); secondly, if it is not empty, it indicates that The histogram h ₁ can be divided again, and the number of blocks that can be divided is 1+length(jg ₁ ). For any block histogram in 1...(1+length(jg ₁ )) is Hx=h ₁ (T1:jg ₁ (i)), the gray level of the corresponding block histogram is idx=id ₁ ( T1:jg ₁ (i)), where i=1...n ₁ -1, the T1 variable takes T1=1 when i=1, and the T1 variable when i=2...n ₁ -1 is the processed jg ₁ (i)+1 of the previous block, that is, T1=1+jg ₁ (i).

(5) Similarly, as in step ( ₄ ), obtain the histogram Hx of each block in the histogram h2. First, judge whether the array jg ₂ is empty (isempty(jg ₂ )==1), if it is empty, it means that the histogram h ₂ cannot be divided, then Hx=h ₂ , idx=id ₂ , and the length of the segment Hx is length( Hx); secondly, if it is not empty, it indicates that the histogram h ₂ can be divided again, and the number of blocks that can be divided is 1+length(jg ₂ ). For any block histogram in 1...(1+length(jg ₂ )) is Hx=h ₂ (T2:jg ₂ (i)), the gray level of the corresponding block histogram is idx=id ₂ ( T2:jg ₂ (i)), where i=1...n ₂ -1, the T2 variable takes T2=1 when i=1, and the T2 variable when i=2...n ₂ -1 is the processed jg ₂ (i)+1 of the previous block, that is, T2=1+jg ₂ (i).

累积概率

其中i＝1...length(Hx)；S5, calculate the probability of each block histogram in the first public array Hx

cumulative probability

where i=1...length(Hx);

S6, the histogram of each block in the first public array Hx is calculated according to the following formula:

where i=1...length(Hx), f(i) is the gray value of the output image, and P ₁ is the adjustment parameter of image detail, brightness, and contrast.

As an optional implementation manner of the embodiment of the present invention, P ₁ has a value range of [0, 1]. Preferred P ₁ =0.1. Specifically, P ₁ can be changed as required, P ₁ can finely adjust the contrast and information entropy of the image, and selecting 0.1 in the actual calculation process can simplify the calculation and improve the calculation speed.

S7, output the output image imageout.

It can be seen that the method for enhancing the image details of the consumer electronic products provided by the embodiment of the present invention adopts the local histogram processing of the automatic histogram segmentation technology, the algorithm is simple and effective, and the brightness of the input image can be well maintained. At the same time, it can achieve image contrast enhancement, clearly present image details, and can be applied to consumer electronic product images and infrared image processing systems that require high brightness maintenance.

2 shows a schematic structural diagram of an image detail enhancement device for maintaining brightness of a consumer electronic product provided by an embodiment of the present invention. The device for enhancing image detail for maintaining brightness of a consumer electronic product provided by an embodiment of the present invention is applied to the above method, The following only briefly describes the structure of the image detail enhancement device for maintaining the brightness of consumer electronic products. The image detail enhancement device for maintaining the brightness of a consumer electronic product provided by the embodiment of the present invention includes:

The first calculation module is used to calculate the grayscale histogram h(i) and the probability p(i) of the grayscale input image I, where i is the grayscale, and the output image imageout is set to be the same size as the input image I, and the numerical value set to zero matrix;

The recording module is used to record the histogram conforming to the first rule by using the first array _h1 , record the corresponding grayscale by using the _first grayscale array id1, and record the histogram conforming to the _second rule by using the second array h2, The corresponding gray level is recorded by using the second gray level array id ₂ , wherein the first rule includes 0<p(i)<=1/255, and the second rule includes: p(i)>1/255;

The segmentation module is used to subdivide the first array h ₁ and the second array h ₂ , use the jgh ₁ array to record the difference between two adjacent numbers in the first grayscale array id ₁ , and use the jg ₁ array to record jgh ₁ ( x)>= the value of the preset value, the size of the number of divided blocks is 1+length(jg ₁ ); use the jgh ₂ array to record the difference between two adjacent numbers in the second grayscale array id ₂ , and use the jg ₂ array to record jgh ₂ (x)>= the value of the preset value, the number of divided blocks is 1+length(jg ₂ );

The determination module is used to set the first public array Hx to store the block histogram, the second public array idx to store the gray level of the first public array Hx, wherein, the acquisition method of each block histogram Hx in the first array h ₁ It is: to judge whether the jg ₁ array is empty, if it is empty, it is determined that the first array h ₁ cannot be divided, then the first public array Hx=h ₁ , the second public array idx=id ₁ , and the first public array Hx stores the The length of the block histogram is length(Hx); if it is not empty, it is determined that the first array h ₁ can be divided again, and the number of divided blocks is 1+length(jg ₁ ). For 1...(1+length( jg ₁ )) in any block histogram is Hx=h ₁ (T1:jg ₁ (i)), and the gray level of the corresponding block histogram is idx=id ₁ (T1:jg ₁ (i)), where i=1...n ₁ -1, when i=1, T1=1, when i=2...n ₁ -1, T1=1+jg ₁ (i); in the second array h ₂ The acquisition method of each block histogram Hx is as follows: judging whether the jg ₂ array is empty, if it is empty, it is determined that the second array h ₂ cannot be divided, then the first public array Hx=h ₂ , the second public array idx=id _2. The length of the block histogram stored in the first public array Hx is length(Hx); if it is not empty, it is determined that the second array h ₂ can be divided again, and the number of divided blocks is 1+length(jg ₂ ). The arbitrary block histogram in 1...(1+length(jg ₂ )) is Hx=h ₂ (T2:jg ₂ (i)), and the gray level of the corresponding block histogram is idx=id ₂ (T2 :jg ₂ (i)), where i=1...n ₂ -1, when i=1, T2=1, when i=2...n ₂ -1, T2=1+jg ₂ ( i);

累积概率

其中i＝1...length(Hx)；The second calculation module is used to calculate the probability of each block histogram in the first public array Hx

cumulative probability

where i=1...length(Hx);

The third calculation module is used to calculate the histogram of each block in the first public array Hx according to the following formula:

where i=1...length(Hx), f(i) is the gray value of the output image, and P ₁ is the adjustment parameter of image detail, brightness, and contrast;

The output module is used to output the output image imageout.

As an optional implementation manner of the embodiment of the present invention, P ₁ has a value range of [0, 1].

As an optional implementation manner of the embodiment of the present invention, P ₁ =0.1.

As an optional implementation manner of the embodiment of the present invention, the preset value is 20.

It can be seen that the image detail enhancement device for maintaining the brightness of consumer electronic products provided by the embodiment of the present invention adopts the local histogram processing of the automatic histogram segmentation technology, the algorithm is simple and effective, and the brightness of the input image can be well maintained. At the same time, it can achieve image contrast enhancement, clearly present image details, and can be applied to consumer electronic product images and infrared image processing systems that require high brightness maintenance.

In order to better illustrate the positive effects of the present invention, the algorithms such as GHE, BBHE, BHEPL, and BHEMHE are compared with the present invention for indicators such as running time, average luminance error (ABME), and peak signal-to-noise ratio (PSNR). The data are: The average value of 20 images was processed, and the data table is shown in Table 1.

GHE BBHE BHEMHE BHEPL this invention time 0.32 0.3934 0.3948 0.4026 0.3378 ABME 43.29 13.39 15.79 6.11 5.5934 PSNR 14.57 20.94 19.54 25.46 28.13

Table 1

It can be seen from Table 1 that the running speed of the present invention is almost the same as that of the classical global histogram (GHE) algorithm, and the average luminance error (ABME) is the smallest, indicating that the enhanced image of the present invention is basically consistent with the input image in terms of brightness; The image peak signal-to-noise ratio (PSNR) is the highest, and the noise suppression is the best.

Meanwhile, FIGS. 3 , 4 , 5 , and 6 show the images before and after processing by the image detail enhancement method for maintaining the brightness of the consumer electronic product provided by the embodiment of the present invention.

The above are merely examples of the present application, and are not intended to limit the present application. Various modifications and variations of this application are possible for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this application shall be included within the scope of the claims of this application.

Claims (8)

1. A method for brightness preserving image detail enhancement for consumer electronics, comprising:

calculating a gray level histogram h (I) and a probability p (I) of a gray level input image I, wherein I is a gray level, setting an output image imageout to be the same as the input image I in size, and setting numerical values to be a zero matrix;

using the first array h₁Recording the histogram according with the first rule, using the first gray level array id₁Recording corresponding gray levels using a second array h₂Recording the histogram according to the second ruleWith second gray level array id₂Recording corresponding gray levels, wherein the first rule comprises 0<p(i)<1/255, the second rule includes: p (i)>1/255；

The first array h₁And said second array h₂Performing subdivision using jgh₁The array records the first gray level array id₁The difference between two adjacent numbers is determined by jg₁Array record jgh₁(x)>Number of division blocks size 1+ length (jg) as a numerical value of a preset value₁) A plurality of; by jgh₂The array records the second gray level array id₂The difference between two adjacent numbers is determined by jg₂Array record jgh₂(x)>Number of division blocks size 1+ length (jg) as a numerical value of a preset value₂) A plurality of;

setting a first public array Hx for storing a block histogram, and setting a second public array idx for storing the gray level of the first public array Hx, wherein the first array h₁The acquisition mode of each block histogram Hx is as follows: judging the jg₁Whether the array is empty or not, if so, determining the first array h₁If the division is impossible, let the first common array Hx be h₁The second public array idx ═ id₁The length of the block histogram stored in the first public array Hx is length (Hx); if not, determining the first array h₁Can be divided again, and the number of divided blocks is 1+ length (jg)₁) 1. (1+ length (jg))₁) H ═ h) for any block histogram₁(T1:jg₁(i) Idx ═ id corresponding to the gray level of the block histogram)₁(T1:jg₁(i) N), wherein i ═ 1.. n)₁-1, when i is 1, T1 is 1, and when i is 2₁1, T1 ═ 1+ jg₁(i) (ii) a The second array h₂The acquisition mode of each block histogram Hx is as follows: judging the jg₂Whether the array is empty or not, if so, determining the second array h₂If the division is impossible, let the first common array Hx be h₂The second public array idx ═ id₂The length of the block histogram stored in the first public array Hx is length (Hx); if not, determining the secondArray h₂Can be divided again, and the number of divided blocks is 1+ length (jg)₂) 1. (1+ length (jg))₂) H ═ h) for any block histogram₂(T2:jg₂(i) Idx ═ id corresponding to the gray level of the block histogram)₂(T2:jg₂(i) N), wherein i ═ 1.. n)₂-1, when i is 1, T2 is 1, and when i is 2₂1, T2 ═ 1+ jg₂(i)；

Calculating the probability of each block histogram in the first public array Hx

Cumulative probability

Length (hx);

calculating the histogram of each block in the first public array Hx according to the following formula:

where i 1.. length (hx), f (i) is the gray value of the output image, P₁Adjusting parameters of image details, brightness and contrast;

and outputting the output image imageout.

2. The method of claim 1, wherein P is P₁Value range [0,1 ]]。

3. The method of claim 2, wherein P is₁＝0.1。

4. The method according to any one of claims 1 to 3, wherein the preset value is 20.

5. An image detail enhancement apparatus for brightness preservation of consumer electronics, comprising:

the first calculation module is used for calculating a gray level histogram h (I) and a probability p (I) of a gray level input image I, wherein I is a gray level, the size of an output image imageout is set to be the same as that of the input image I, and the numerical value is set to be a zero matrix;

a recording module for utilizing the first array h₁Recording the histogram according with the first rule, using the first gray level array id₁Recording corresponding gray levels using a second array h₂Recording the histogram according with the second rule, and using the second gray level array id₂Recording corresponding gray levels, wherein the first rule comprises 0<p(i)<1/255, the second rule includes: p (i)>1/255；

A partitioning module for partitioning the first array h₁And said second array h₂Performing subdivision using jgh₁The array records the first gray level array id₁The difference between two adjacent numbers is determined by jg₁Array record jgh₁(x)>Number of division blocks size 1+ length (jg) as a numerical value of a preset value₁) A plurality of; by jgh₂The array records the second gray level array id₂The difference between two adjacent numbers is determined by jg₂Array record jgh₂(x)>Number of division blocks size 1+ length (jg) as a numerical value of a preset value₂) A plurality of;

a determining module, configured to set a first public array Hx storing a block histogram, and a second public array idx storing a gray level of the first public array Hx, where the first array h₁The acquisition mode of each block histogram Hx is as follows: judging the jg₁Whether the array is empty or not, if so, determining the first array h₁If the division is impossible, let the first common array Hx be h₁The second public array idx ═ id₁The length of the block histogram stored in the first public array Hx is length (Hx); if not, determining the first array h₁Can be divided again, and the number of divided blocks is 1+ length (jg)₁) 1. (1+ length (jg))₁) H ═ h) for any block histogram₁(T1:jg₁(i) Corresponding to a block histogram having a gray level idx ═ yid₁(T1:jg₁(i) N), wherein i ═ 1.. n)₁-1, when i is 1, T1 is 1, and when i is 2₁1, T1 ═ 1+ jg₁(i) (ii) a The second array h₂The acquisition mode of each block histogram Hx is as follows: judging the jg₂Whether the array is empty or not, if so, determining the second array h₂If the division is impossible, let the first common array Hx be h₂The second public array idx ═ id₂The length of the block histogram stored in the first public array Hx is length (Hx); if not, determining the second array h₂Can be divided again, and the number of divided blocks is 1+ length (jg)₂) 1. (1+ length (jg))₂) H ═ h) for any block histogram₂(T2:jg₂(i) Idx ═ id corresponding to the gray level of the block histogram)₂(T2:jg₂(i) N), wherein i ═ 1.. n)₂-1, when i is 1, T2 is 1, and when i is 2₂1, T2 ═ 1+ jg₂(i)；

A second calculating module for calculating the probability of each block histogram in the first public array Hx

Cumulative probability

Length (hx);

a third calculating module, configured to calculate the histogram of each block in the first common array Hx according to the following formula:

where i 1.. length (hx), f (i) is the gray value of the output image, P₁Adjusting parameters of image details, brightness and contrast;

and the output module is used for outputting the output image imageout.

6. According to claim 5The apparatus of, wherein P is₁Value range [0,1 ]]。

7. The apparatus of claim 6, wherein P is₁＝0.1。

8. The device according to any one of claims 5 to 7, characterized in that said preset value is 20.

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