CN106127694B - Adaptive two-way guarantor's bandwidth logarithmic transformation method of uneven illumination image enhancement - Google Patents
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Abstract
一种照度不均图像增强的自适应双向保带宽对数变换方法，其特征在于包括下列步骤：步骤1：输入照度不均的图像，并对该图像进行标准化变换；步骤2：计算标准化变换后图像的平均亮度AL，并根据AL的值对该图像进行双向保带宽对数变换：若AL<127.5，则先进行反向保带宽对数变换，再进行正向保带宽对数变换；否则，则先进行正向保带宽对数变换，再进行反向保带宽对数变换；步骤3：取整变换；步骤4：输出图像。本发明的特点是:具有增强暗区对比度和亮区对比度的优点，增强效果明显，而且背景保留良好，完全无光晕现象，使图像质量得到整体增强。
An adaptive two-way bandwidth-preserving logarithmic transformation method for image enhancement with uneven illumination, which is characterized in that it includes the following steps: Step 1: Input an image with uneven illumination, and perform standardized transformation on the image; Step 2: Calculate the normalized transformation The average brightness AL of the image, and perform two-way bandwidth-preserving logarithmic transformation on the image according to the value of AL: if AL<127.5, first perform the reverse bandwidth-preserving logarithmic transformation, and then perform the forward bandwidth-preserving logarithmic transformation; otherwise, First perform forward bandwidth-preserving logarithmic transformation, and then perform reverse bandwidth-preserving logarithmic transformation; step 3: rounding transformation; step 4: output image. The present invention is characterized in that it has the advantages of enhancing the contrast of the dark area and the bright area, the enhancement effect is obvious, the background is well preserved, and there is no halo phenomenon at all, so that the overall image quality is enhanced.
Description
技术领域technical field
本发明属于数字图像处理领域，涉及一种对照度不均图像的质量增强方法。The invention belongs to the field of digital image processing and relates to a method for enhancing the quality of images with uneven illumination.
背景技术Background technique
由于人类视觉对过高或过低亮度图像的对比度敏感性降低，所以需要对过暗或过亮图像(或区域)进行对比度增强，以便感知其细节。而照度不均的图像，既有过高亮区又有过低暗区，一般的方法效果不好，有的还会出现光晕现象。Since human vision is less sensitive to the contrast of images with too high or too low brightness, it is necessary to enhance the contrast of too dark or too bright images (or regions) in order to perceive their details. For images with uneven illumination, there are both high-bright areas and low-dark areas, the general method is not effective, and some halos will appear.
目前，采用对数方法增强图像质量，在图像处理各个领域已得到广泛的使用和研究。已公开专利中，如：保持颜色的去雾方法(申请号：CN101754032A)，一种降低合成孔径雷达影像斑点噪声的方法(申请号：CN101398487A)，一种水下降质图像的自适应增强方法(CN104766285A)，等。这些方法都是采用单向(正向)对数变换作为图像预处理方法，再结合去雾、去噪、去水等其他方法用于图像增强，计算方法复杂，处理时间长，会增强非原始图像中所含有的信息。At present, the use of logarithmic methods to enhance image quality has been widely used and researched in various fields of image processing. Among the published patents, such as: a color-preserving defogging method (application number: CN101754032A), a method for reducing speckle noise in synthetic aperture radar images (application number: CN101398487A), an adaptive enhancement method for underwater degradation images ( CN104766285A), etc. These methods all use one-way (forward) logarithmic transformation as the image preprocessing method, combined with other methods such as dehazing, denoising, dewatering, etc. for image enhancement, the calculation method is complicated, and the processing time is long, which will enhance the non-original information contained in the image.
在已发表的文献中，涉及图像对数变换的文献较多，主要有LIP(logarithmicimage processing)家族(指以LIP为基础各种变形和改进)方法和RETINEX家族(指以RETINEX为基础各种变形和改进)方法。这些方法也只是进行的单向的对数变换，只能拉开灰度/色度谱(或称为直方图)低端(暗区)的谱线间的距离，因而只能提高图像低端(暗区)的对比度，达到图像对比度增强的目的。同时，它们还包含两图像相减的计算，可能产生负的数据，破坏了图像的正定特征，并可能引入源图像中并不存在的附加信息，破坏了保真性，引起组成成份失真。In the published literature, there are many literatures related to image logarithmic transformation, mainly including the LIP (logarithmic image processing) family (referring to various deformations and improvements based on LIP) and the RETINEX family (referring to various deformations based on RETINEX). and improved) method. These methods are only one-way logarithmic transformations, which can only increase the distance between the spectral lines at the low end (dark area) of the grayscale/chromaticity spectrum (or called histogram), thus only improving the low end of the image. (dark area) contrast to achieve the purpose of image contrast enhancement. At the same time, they also include the calculation of the subtraction of two images, which may generate negative data, destroy the positive features of the image, and may introduce additional information that does not exist in the source image, destroying fidelity and causing component distortion.
因此，目前采用的对数方法进行图像增强的缺陷是没有涉及如何提高高端(亮区)的对比度，且不增加原图中所含信息(强调保真性)。Therefore, the defect of the current logarithmic method for image enhancement is that it does not involve how to improve the contrast of the high-end (bright area), and does not increase the information contained in the original image (emphasis on fidelity).
发明内容Contents of the invention
本发明的目的是提供一种用于照度不均的图像视觉质量增强的自适应双向保带宽对数变换方法，不仅能够提高暗区的对比度，还能提高亮区的对比度，不产生光晕现象，达到更好的、且不增加图像信息图像增强的效果。The purpose of the present invention is to provide an adaptive two-way bandwidth-preserving logarithmic transformation method for enhancing the visual quality of images with uneven illumination, which can not only improve the contrast of dark areas, but also improve the contrast of bright areas without halo phenomenon , to achieve a better effect of image enhancement without increasing image information.
为达到本发明的目的，本发明提出一种照度不均图像增强的自适应双向保带宽对数变换方法，其关键在于包括下列步骤：In order to achieve the purpose of the present invention, the present invention proposes a kind of self-adaptive two-way bandwidth-preserving logarithmic transformation method of uneven illumination image enhancement, and its key is to comprise the following steps:
步骤1：输入照度不均的图像，并对该图像进行标准化变换，得到标准化变换后图像；Step 1: Input an image with uneven illumination, and perform standardized transformation on the image to obtain a standardized transformed image;
标准化变换的方法参见《标准化图像的生成方法》(公开号：CN102800062A)。标准化变换后，图像变为具有全带宽特性的图像。这是本发明实施的基础。For the method of normalized transformation, refer to "Method for Generating Standardized Image" (publication number: CN102800062A). After the normalization transformation, the image becomes an image with full bandwidth characteristics. This is the basis for the implementation of the present invention.
步骤2：计算标准化变换后图像的平均亮度AL，并根据AL的值对该图像进行双向保带宽对数变换：Step 2: Calculate the average brightness AL of the image after normalization transformation, and perform bidirectional bandwidth-preserving logarithmic transformation on the image according to the value of AL:
平均亮度AL是本发明的自适应参数，随图像不同而不同，不需要人工设定。The average brightness AL is an adaptive parameter of the present invention, which varies with different images and does not need to be set manually.
所述双向保带宽对数变换，由正向保带宽对数变换和反向保带宽对数变换组成，所述对数变换的底数为1.02198395689；The bidirectional bandwidth-preserving logarithmic transformation is composed of a forward bandwidth-preserving logarithmic transformation and a reverse bandwidth-preserving logarithmic transformation, and the base of the logarithmic transformation is 1.02198395689;
若AL<127.5，则先进行反向保带宽对数变换，再进行正向保带宽对数变换；If AL<127.5, perform reverse bandwidth-preserving logarithmic transformation first, and then perform forward bandwidth-preserving logarithmic transformation;
否则，则先进行正向保带宽对数变换，再进行反向保带宽对数变换；Otherwise, the forward bandwidth-preserving logarithmic transformation is performed first, and then the reverse bandwidth-preserving logarithmic transformation is performed;
步骤3：对双向保带宽对数变换后的图像进行取整变换；Step 3: Carry out rounding transformation to the image after bidirectional bandwidth-preserving logarithmic transformation;
图像进行双向保带宽对数变换后，图像的灰度/色度值变为实数，不能满足图像显示的要求，因此需要进行取整变换，将图像的灰度/色度值变为整数。取整变换采用四舍五入的方式。After the image undergoes two-way bandwidth-preserving logarithmic transformation, the grayscale/chromaticity value of the image becomes a real number, which cannot meet the requirements of image display. Therefore, rounding transformation is required to convert the grayscale/chromaticity value of the image into an integer. The rounding conversion adopts the rounding method.
步骤4：输出图像。Step 4: Output image.
所述正向保带宽对数变换按以下方式进行：The forward bandwidth-preserving logarithmic transformation is carried out in the following manner:
步骤一：对需变换的图像f(x,y)进行右移变换，得到右移变换后的图像F(x,y)；Step 1: Perform right-shift transformation on the image f(x, y) to be transformed, and obtain the image F(x, y) after right-shift transformation;
所述右移变换按下式进行：The right shift transformation is carried out as follows:
F(x,y)＝SHIFTR1[f(x,y)]＝f(x,y)+1F(x,y)=SHIFTR1[f(x,y)]=f(x,y)+1
其中，SHIFTR1[·]表示沿x轴右移1位的移位算符；F(x,y)，f(x,y)为整数矩阵；f(x,y)中元素的值域为0～255，F(x,y)中元素的值域变为1～256；Among them, SHIFTR1[ ] represents a shift operator that shifts 1 bit to the right along the x-axis; F(x,y), f(x,y) is an integer matrix; the value range of elements in f(x,y) is 0 ~255, the value range of elements in F(x,y) becomes 1~256;
步骤二：将右移变换后的图像F(x,y)进行正向对数变换，得到正向对数变换后的图像 Step 2: Perform forward logarithmic transformation on the image F(x, y) after the right shift transformation, and obtain the image after forward logarithmic transformation
所述正向对数变换按下式进行：The forward logarithmic transformation is carried out as follows:
其中，LOGa[·]表示取以a为底的对数的算符；是实数矩阵；a＝1.02198395689。Among them, LOG a [·] represents the operator taking the logarithm with base a as the base; is a real number matrix; a=1.02198395689.
所述反向保带宽对数变换按以下方式进行：The reverse bandwidth-preserving logarithmic transformation is carried out in the following manner:
步骤一：对需变换的图像f(x,y)进行补变换，获得补图像Ψ(x,y)；Step 1: Complementary transformation is performed on the image f(x,y) to be transformed to obtain the complementary image Ψ(x,y);
所述补变换按下式进行：The complementary transformation is carried out as follows:
Ψ(x,y)＝255-f(x,y)Ψ(x,y)=255-f(x,y)
其中，Ψ(x,y)，f(x,y)为整数矩阵，两整数矩阵中元素的值域均为0～255；Among them, Ψ(x, y), f(x, y) are integer matrices, and the value ranges of the elements in the two integer matrices are both 0-255;
步骤二：对补图像Ψ(x,y)进行右移变换，得到右移变换后的图像F1(x,y)；Step 2: Perform right-shift transformation on the complementary image Ψ(x, y) to obtain the image F1(x, y) after right-shift transformation;
所述右移变换按下式进行：The right shift transformation is carried out as follows:
F1(x,y)＝SHIFTR1[Ψ(x,y)]＝Ψ(x,y)+1F1(x,y)=SHIFTR1[Ψ(x,y)]=Ψ(x,y)+1
其中，SHIFTR1[·]表示沿x轴右移1位的移位算符；F1(x,y)为整数矩阵，元素的值域变为1～256；Among them, SHIFTR1[ ] represents a shift operator that shifts 1 bit to the right along the x-axis; F1(x,y) is an integer matrix, and the value range of elements becomes 1 to 256;
步骤三：将右移变换后的图像F1(x,y)进行正向对数变换，得到正向对数变换后的图像 Step 3: Perform forward logarithmic transformation on the right-shifted image F1(x,y) to obtain the image after forward logarithmic transformation
所述正向对数变换按下式进行：The forward logarithmic transformation is carried out as follows:
其中，LOGa[·]表示取以a为底的对数的算符；是实数矩阵；a＝1.02198395689；Among them, LOG a [·] represents the operator taking the logarithm with base a as the base; is a real number matrix; a=1.02198395689;
步骤四，对按步骤一进行补变换，得到正图像。step four, yes Complementary transformation is performed according to step 1 to obtain a positive image.
所述正图像是相对于补图像而言。未经过补变换的图像，认为是正图像，对补图像再次进行补变换，得到的也是正图像。The positive image is relative to the complementary image. The image that has not undergone complementary transformation is considered to be a positive image, and the complementary image is processed again to obtain a positive image.
一般的数字图像的像素的灰度/色度在0～255间取值(所谓8位系统)，0的对数表示不确定性，所以在做对数变换前需对图像灰度/色度谱进行右移变换，以消除对数变换的不确定性。右移变换后，图像的灰度/色度值的取值范围从0～255变为1～256。The grayscale/chromaticity of a pixel in a general digital image takes a value between 0 and 255 (the so-called 8-bit system), and the logarithm of 0 represents uncertainty, so the grayscale/chromaticity of the image needs to be adjusted before logarithmic transformation The spectrum is right-shifted to eliminate the uncertainty of the logarithmic transformation. After the right-shift transformation, the value range of the grayscale/chromaticity value of the image changes from 0 to 255 to 1 to 256.
沿x轴的正向的对数变换称为正向对数变换。正向对数变换有增加灰度/色度谱低端(图像暗区)对比度的功能。A logarithmic transformation in the positive direction along the x-axis is called a forward logarithmic transformation. The forward logarithmic transformation has the function of increasing the contrast at the low end of the gray/chromatic spectrum (dark areas of the image).
沿x轴的负向的对数变换称为反向对数变换。反向对数变换有增加灰度/色度谱高端(图像亮区)对比度的功能。由于补图像的正向对数变换等效于原图像的反向对数变换，因此，图像的反向对数变换可以用其补图像的正向对数变换实现，以提高灰度/色度谱高端(图像亮区)的对比度。The logarithmic transformation along the negative direction of the x-axis is called the inverse logarithmic transformation. The inverse logarithmic transformation has the function of increasing contrast at the high end of the grayscale/chromatic spectrum (bright areas of the image). Since the forward logarithmic transformation of the complementary image is equivalent to the reverse logarithmic transformation of the original image, the reverse logarithmic transformation of the image can be realized by the forward logarithmic transformation of its complementary image to improve the grayscale/chroma Contrast at the high end of the spectrum (bright areas of the image).
对数变换后的图像的灰度/色度谱的带宽随对数底数a的变而变化。在作对数变换时，取底数a＝1.02198395689，是实现保带宽的决定因素。The bandwidth of the grayscale/chromaticity spectrum of the logarithmically transformed image varies with the base a of the logarithm. When doing logarithmic transformation, the base number a=1.02198395689 is the decisive factor for realizing the bandwidth preservation.
下表给出了a取值不同时，M＝Loga256及带宽的不同结果：The following table shows the different results of M=Log a 256 and bandwidth when the value of a is different:
从上表中可以看出，a＝1.02198395689是一个特殊的对数底数，右移变换后图像在以此为底的对数变换后，低端对比度提升，自动产生了左移一位的操作，灰度/色度谱还原成原带宽0～255。It can be seen from the above table that a=1.02198395689 is a special logarithmic base. After the right-shifted image is logarithmically transformed with this as the base, the low-end contrast is improved, and the operation of shifting one bit to the left is automatically generated. The grayscale/chromaticity spectrum is restored to the original bandwidth of 0-255.
图像的以a＝1.02198395689为底的特殊对数变换，称为保带宽对数变换。保持0～255的最大带宽就提供了具有最大对比度的可能性。The special logarithmic transformation of the image based on a=1.02198395689 is called bandwidth-preserving logarithmic transformation. Maintaining a maximum bandwidth of 0 to 255 provides the possibility to have maximum contrast.
本发明的显著效果是：利用标准化变换、平均亮度计算、右移变换、由正向对数变换和反向对数变换组成的双向对数变换、由选择对数的底数实现的保带宽变换这几种方法，对照度不均的图像进行了很好的增强作用。该方法不仅具有增强暗区对比度和亮区对比度的优点，增强效果明显，而且背景保留良好，完全无光晕现象，使图像质量得到整体增强。The notable effect of the present invention is: utilize standardization transformation, average brightness calculation, right-shift transformation, two-way logarithmic transformation consisting of forward logarithmic transformation and reverse logarithmic transformation, bandwidth-preserving transformation realized by selecting the base number of logarithm. Several methods have performed a good enhancement on images with uneven illumination. This method not only has the advantages of enhancing the contrast of dark areas and bright areas, but the enhancement effect is obvious, and the background is well preserved, and there is no halo phenomenon at all, so that the overall image quality is enhanced.
附图说明Description of drawings
图1本发明的流程图；Fig. 1 flow chart of the present invention;
图2(a-1)、(b-1)、(c-1)是实施例1中的源图像；Fig. 2 (a-1), (b-1), (c-1) is the source image in embodiment 1;
图2(a-2)、(b-2)、(c-2)分别是图2(a-1)、(b-1)、(c-1)经自适应双向保带宽对数变换方法变换后的图像；Fig. 2 (a-2), (b-2), (c-2) are respectively Fig. 2 (a-1), (b-1), (c-1) through adaptive two-way bandwidth-preserving logarithmic transformation method transformed image;
图2(a-3)、(b-3)、(c-3)是图2(a-1)、(b-1)、(c-1)经Zadeh-X(见中国发明专利《底层图像挖掘中获取最佳质量图像的方法》，公开号:CN101419707)方法增强后的图像。Fig. 2 (a-3), (b-3), (c-3) is Fig. 2 (a-1), (b-1), (c-1) through Zadeh-X (see Chinese invention patent " bottom layer The method for obtaining the best quality image in image mining", publication number: CN101419707) method enhanced image.
具体实施方式Detailed ways
下面结合附图和具体实施例对本发明作进一步详细说明。The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.
实施例1：如图1所示的流程：一种照度不均图像增强的自适应双向保带宽对数变换方法，包括下列步骤：Embodiment 1: the flow process as shown in Figure 1: a kind of self-adaptive two-way band-preserving logarithmic transformation method of uneven illumination image enhancement, comprising the following steps:
步骤1：输入照度不均的图像，并对该图像进行标准化变换，得到标准化变换后图像；Step 1: Input an image with uneven illumination, and perform standardized transformation on the image to obtain a standardized transformed image;
标准化变换的方法参见《标准化图像的生成方法》(公开号：CN102800062A)。For the method of normalized transformation, refer to "Method for Generating Standardized Image" (publication number: CN102800062A).
步骤2：计算标准化变换后图像的平均亮度AL，并根据AL的值对该图像进行双向保带宽对数变换：Step 2: Calculate the average brightness AL of the image after normalization transformation, and perform bidirectional bandwidth-preserving logarithmic transformation on the image according to the value of AL:
平均亮度AL是本发明的自适应参数；The average brightness AL is an adaptive parameter of the present invention;
所述双向保带宽对数变换，由正向保带宽对数变换和反向保带宽对数变换组成，所述对数变换的底数为1.02198395689；The bidirectional bandwidth-preserving logarithmic transformation is composed of a forward bandwidth-preserving logarithmic transformation and a reverse bandwidth-preserving logarithmic transformation, and the base of the logarithmic transformation is 1.02198395689;
若AL<127.5，则先进行反向保带宽对数变换，再进行正向保带宽对数变换；If AL<127.5, perform reverse bandwidth-preserving logarithmic transformation first, and then perform forward bandwidth-preserving logarithmic transformation;
否则，则先进行正向保带宽对数变换，再进行反向保带宽对数变换。Otherwise, the forward bandwidth-preserving logarithmic transformation is performed first, and then the reverse bandwidth-preserving logarithmic transformation is performed.
所述正向保带宽对数变换按以下方式进行：The forward bandwidth-preserving logarithmic transformation is carried out in the following manner:
步骤一：对需变换的图像f(x,y)进行右移变换，得到右移变换后的图像F(x,y)；Step 1: Perform right-shift transformation on the image f(x, y) to be transformed, and obtain the image F(x, y) after right-shift transformation;
所述右移变换按下式进行：The right shift transformation is carried out as follows:
F(x,y)＝SHIFTR1[f(x,y)]＝f(x,y)+1F(x,y)=SHIFTR1[f(x,y)]=f(x,y)+1
其中，SHIFTR1[·]表示沿x轴右移1位的移位算符；F(x,y)，f(x,y)为整数矩阵；f(x,y)中元素的值域为0～255，F(x,y)中元素的值域变为1～256；Among them, SHIFTR1[ ] represents a shift operator that shifts 1 bit to the right along the x-axis; F(x,y), f(x,y) is an integer matrix; the value range of elements in f(x,y) is 0 ~255, the value range of elements in F(x,y) becomes 1~256;
步骤二：将右移变换后的图像F(x,y)进行正向对数变换，得到正向对数变换后的图像 Step 2: Perform forward logarithmic transformation on the image F(x, y) after the right shift transformation, and obtain the image after forward logarithmic transformation
所述正向对数变换按下式进行：The forward logarithmic transformation is carried out as follows:
其中，LOGa[·]表示取以a为底的对数的算符；是实数矩阵；a＝1.02198395689。Among them, LOG a [·] represents the operator taking the logarithm with base a as the base; is a real number matrix; a=1.02198395689.
所述反向保带宽对数变换按以下方式进行：The reverse bandwidth-preserving logarithmic transformation is carried out in the following manner:
步骤一：对需变换的图像f(x,y)进行补变换，获得补图像Ψ(x,y)；Step 1: Complementary transformation is performed on the image f(x,y) to be transformed to obtain the complementary image Ψ(x,y);
所述补变换按下式进行：The complementary transformation is carried out as follows:
Ψ(x,y)＝255-f(x,y)Ψ(x,y)=255-f(x,y)
其中，Ψ(x,y)，f(x,y)为整数矩阵，两整数矩阵中元素的值域均为0～255；Among them, Ψ(x, y), f(x, y) are integer matrices, and the value ranges of the elements in the two integer matrices are both 0-255;
步骤二：对补图像Ψ(x,y)进行右移变换，得到右移变换后的图像F1(x,y)；Step 2: Perform right-shift transformation on the complementary image Ψ(x, y) to obtain the image F1(x, y) after right-shift transformation;
所述右移变换按下式进行：The right shift transformation is carried out as follows:
F1(x,y)＝SHIFTR1[Ψ(x,y)]＝Ψ(x,y)+1F1(x,y)=SHIFTR1[Ψ(x,y)]=Ψ(x,y)+1
其中，SHIFTR1[·]表示沿x轴右移1位的移位算符；F1(x,y)为整数矩阵，元素的值域变为1～256；Among them, SHIFTR1[ ] represents a shift operator that shifts 1 bit to the right along the x-axis; F1(x,y) is an integer matrix, and the value range of elements becomes 1 to 256;
步骤三：将右移变换后的图像F1(x,y)进行正向对数变换，得到正向对数变换后的图像 Step 3: Perform forward logarithmic transformation on the right-shifted image F1(x,y) to obtain the image after forward logarithmic transformation
所述正向对数变换按下式进行：The forward logarithmic transformation is carried out as follows:
其中，LOGa[·]表示取以a为底的对数的算符；是实数矩阵；a＝1.02198395689；Among them, LOG a [·] represents the operator taking the logarithm with base a as the base; is a real number matrix; a=1.02198395689;
步骤四，对按步骤一进行补变换，得到正图像。step four, yes Complementary transformation is performed according to step 1 to obtain a positive image.
所述正图像是相对于补图像(或称为负图像，负像，负片)而言。未经过补变换的图像，认为是正图像，对补图像再次进行补变换，得到的也是正图像。The positive image is relative to the complementary image (or called negative image, negative image, negative film). The image that has not undergone complementary transformation is considered to be a positive image, and the complementary image is processed again to obtain a positive image.
步骤3：对双向保带宽对数变换后的图像进行取整变换；取整变换采用四舍五入的方式。Step 3: Perform rounding transformation on the image after bidirectional bandwidth-preserving logarithmic transformation; the rounding transformation adopts a rounding method.
步骤4：输出图像。Step 4: Output image.
下表列出了图(a-1)、(b-1)、(c-1)以及它们经自适应双向保带宽对数变换方法变换后图像(a-2)、(b-2)、(c-2)平均信息熵AIE，平均对比度AC，平均亮度AL，图像质量评价函数CAF，以上参数的计算可以参见发明专利《彩色图像质量评价方法》(公开号：CN101650833B)：The following table lists the pictures (a-1), (b-1), (c-1) and their transformed images (a-2), (b-2), (c-2) Average information entropy AIE, average contrast AC, average brightness AL, image quality evaluation function CAF, the calculation of the above parameters can be found in the invention patent "color image quality evaluation method" (public number: CN101650833B):
从上表中可以看到，源图像(a-1)、(b-1)的平均亮度AL均<127.5，因此采用先反向后正向的保带宽对数变换。变换后，基本参数两升(AC，AL)一降(AIE)。图像视觉质量增强，是自然过程(图像质量退化，如噪声污染，模糊，使AIE增加)的逆过程，AIE应该减少而不能增加。图像视觉质量评价参数(CAF)升高，提示总的视觉质量增加。It can be seen from the above table that the average luminance AL of the source images (a-1) and (b-1) are both <127.5, so the band-preserving logarithmic transformation is adopted first reverse and then forward. After transformation, the basic parameters are two up (AC, AL) and one down (AIE). Image visual quality enhancement is the inverse process of natural process (image quality degradation, such as noise pollution, blurring, increasing AIE), and AIE should be reduced rather than increased. The image visual quality assessment parameter (CAF) increased, suggesting that the overall visual quality increased.
从图2中也可以看出，采用Zadeh-X方法增强后的图像有光晕现象(图(a-3)尤明显)，暗区增强不足，背景消失(图(b-3)尤明显)。自适应双向保带宽对数变换方法变换后图像(图(a-2)和图(b-2))暗区对比度和亮度增强明显，背景保留良好，完全无光晕现象，整体图像质量明显增强。It can also be seen from Figure 2 that the image enhanced by the Zadeh-X method has a halo phenomenon (especially obvious in Figure (a-3)), the dark area is not enhanced enough, and the background disappears (especially in Figure (b-3)) . Adaptive two-way bandwidth-preserving logarithmic transformation method transforms the image (Figure (a-2) and Figure (b-2)) The contrast and brightness of the dark area are significantly enhanced, the background is well preserved, there is no halo phenomenon at all, and the overall image quality is significantly enhanced .
如上表所示，源图像(c-1)的平均亮度AL>127.5，属于高亮度(AL＝198.2702)照度不均图像。因此需要采用先正向后反向的保带宽对数变换，变换后，图像的信息是减少的(信息熵从源图像的5.8298，减至自适应双向保带宽对数变换方法变换后图像的5.2832)，因为这是逆自然过程。变换结果图像视觉质量评价参数(CAF)升高(15.6336/16.7722)，提示总的视觉质量增加。亮度是减少的(198.2702/138.4668)，趋近于理想值127.5。As shown in the table above, the source image (c-1) has an average luminance AL>127.5, which belongs to a high-brightness (AL=198.2702) uneven illumination image. Therefore, it is necessary to adopt the bandwidth-preserving logarithmic transformation of the forward and reverse. After the transformation, the information of the image is reduced (the information entropy is reduced from 5.8298 of the source image to 5.2832 of the image transformed by the adaptive two-way bandwidth-preserving logarithmic transformation method. ), because this is an anti-natural process. The visual quality evaluation parameter (CAF) of the transformation result image increased (15.6336/16.7722), suggesting that the overall visual quality increased. The brightness is reduced (198.2702/138.4668), approaching the ideal value of 127.5.
图2(c-3)中所示图像有明显光晕现象，亮区增强不足，对比度低。图2(c-2)明显背景对比度增强，完全无光晕现象，整体图像质量增强。The image shown in Figure 2(c-3) has obvious halo phenomenon, insufficient enhancement of bright areas, and low contrast. In Figure 2(c-2), the contrast of the background is obviously enhanced, there is no halo phenomenon at all, and the overall image quality is enhanced.
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