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Image enhancement method and system for histogram equalization interpolation
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A technology of histogram equalization and image enhancement, applied in the field of image processing, can solve the problems of loss of image details, reduction of image gray level, rigid visual effects, etc., to achieve detail information protection, prevention of swallowing, and good brightness retention. Effect
Active Publication Date: 2017-10-20
JIANGSU UNIV OF TECH
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Although the histogram equalizationalgorithm has the advantages of fast calculation speed and obvious enhancement effect, there are also gray levels that are merged, resulting in the reduction and loss of the gray level of the image, the phenomenon of gray level faults, and the loss of valuable details of the image. , the disadvantage of blunt visual effect
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Embodiment 1
[0046] Such as figure 1 As shown, the present embodiment 1 provides an image enhancement method for histogram equalization interpolation, comprising the following steps:
[0047] Step S1, calculating the total number of gray levels q swallowed by the original image I in its enhanced image J;
[0048] Step S2, obtain a new histogram array H' according to the corresponding interval value g of adjacent gray levels in the enhanced image J, and the total number of swallowed gray levels q I (k); and
[0049] Step S3, for the new histogram array H' I (k) Carry out cumulative summation to form a new enhanced image W through the new gray level k'.
[0050] Specifically, the method for calculating the total number of gray levels swallowed by the original image I in its enhanced image J in the step S1 includes the following steps:
[0051] Step S11, counting the histogram array H of the original image I I(k) is not zero gray level total number is s, and wherein, k=I (i, j), i, j are...
Embodiment 2
[0083] Such as Figure 4 As shown, on the basis of embodiment 1, embodiment 2 provides an image enhancement system for histogram equalization interpolation, including:
[0084] A calculation unit for calculating the total number of gray levels q swallowed by the original image I in its enhanced image J, a new histogram array acquisition unit connected to the calculation unit, and a new enhanced image connected to the new histogram array acquisition unit unit; wherein the new histogram array obtaining unit is adapted to obtain a new histogram array H' according to the corresponding interval value g of adjacent gray levels in the enhanced image J, and the total number of swallowed gray levels q I (k);
[0085] The new enhanced image constituting unit is suitable for the new histogram array H' I (k) Carry out cumulative summation to form a new enhanced image W through the new gray level k'.
[0086] Specifically, the calculation unit includes: a first calculation module, which...
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Abstract
The present invention relates to an image enhancement method and system for histogramequalization interpolation. The image enhancement method includes the following steps: step S1, calculating the total number of gray levels q swallowed by the original image I in its enhanced image J; step S2, according to Enhancing the corresponding interval value g of adjacent gray levels in the image J, and the total number of gray levels q swallowed to obtain a new histogram array H'I(k); and step S3, for the new histogram array H'I(k ) for cumulative summation to form a new enhanced image W through the new gray level k'. The present invention can prevent image gray-scale phagocytosis under the condition of keeping the image entropy as constant as possible, and effectively enhance the image, even if the gray-scale in the image is well preserved, the detail information is well protected, and the brightness retention is good. , Image visual soft.
Description
technical field [0001] The invention relates to an image enhancement technology, which belongs to the field of image processing, in particular to an image enhancement method of histogram equalization. Background technique [0002] Histogramequalization method has become a common method of image enhancement because of its effectiveness and ease of use. The basic idea is to determine the corresponding grayscale output value of the image according to the grayscale probability distribution of the input image, and improve the visual effect of the image by expanding the dynamic range of the grayscale distribution of the image, so as to achieve the purpose of improving the contrast of the image. Although the histogram equalizationalgorithm has the advantages of fast calculation speed and obvious enhancement effect, there are also gray levels that are merged, resulting in the reduction and loss of the gray level of the image, the phenomenon of gray level faults, and the loss of va...
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