TWI676962B - Contrast enhancement method and apparatus thereof based on histogram adjustment - Google Patents

Abstract

The invention provides a contrast enhancement method and device based on histogram adjustment. The contrast enhancement device includes an image capturer and an image processor. The image capturer sequentially captures an input brightness value at each pixel position in an input image. The image processor enhances the number of occurrences of the dark areas (that is, the lower brightness parts) in the histogram, and then performs a global mapping according to a critical brightness in the histogram to increase the brightness of the dark areas and maintain the bright areas ( That is, the brightness of the higher brightness part), and a brightness output value is generated accordingly. In this way, the contrast enhancement method and its device can avoid the occurrence of the conventional halo phenomenon, and can adjust the brightness of the dark area without affecting the brightness of the bright area, thereby achieving better contrast enhancement.

Description

Contrast enhancement method and device based on histogram adjustment

The invention provides a contrast enhancement method and a device thereof, and in particular, relates to a contrast enhancement method and a device based on histogram adjustment.

High-contrast images tend to dim their backlights. If you want to brighten the dark areas (that is, the lower brightness parts) without affecting the details of the bright areas (that is, the higher brightness parts), the conventional wide dynamic range method is generally used to enhance the dark areas of the image. These methods all use a variety of frames with different exposure levels to synthesize an image with the most appropriate brightness to increase the brightness of dark areas. However, the WDR method relies heavily on the segmentation of image objects. If the objects in the dark area cannot be accurately separated from the objects in the bright area, the entire image will have a smear effect, which refers to the extent of incorrect exposure on the boundary of the object in the image.

In addition, the conventional histogram equalization (Histogram Equalization) is also commonly used to process the global contrast of the image, using the redistribution of the overall brightness to find a global curve, adjusting the too dark or too bright image area to a visually visible condition There will be no halo phenomenon, and the global contrast can be improved. However, the conventional histogram equalization cannot specifically deal with the dark areas, that is, when the original contrast of the image is already high, after the conventional histogram equalization, the image will not change in any way, and the dark areas There will be no improvement.

Therefore, if you can accurately brighten the dark areas without affecting the fineness of the bright areas, And the entire image will not produce halo, and the image will achieve better contrast enhancement.

The present invention provides a contrast enhancement method and device based on histogram adjustment, which performs histogram statistics on a single image and adjusts the statistics in the histogram statistics to avoid the occurrence of the conventional halo phenomenon. The brightness of the dark area is adjusted without affecting the brightness of the bright area, thereby achieving better contrast enhancement.

An embodiment of the present invention provides a contrast enhancement method based on histogram adjustment, which is applicable to a contrast enhancement device and is used to enhance the contrast of an input image. The contrast enhancement method includes the following steps: (A) receiving an input brightness value of each pixel position in the input image; (B) corresponding to a number of occurrences of each input brightness value to a plurality of brightness values on a histogram; ( C) enhancing the number of occurrences corresponding to at least one brightness value less than a preset brightness value, and each brightness value corresponding to an update appearance number; (D) sequentially accumulating each occurrence number to generate a first accumulation curve, and Accumulate the number of occurrences of each update in order to generate a second accumulation line, wherein the first accumulation curve represents the relationship between the brightness values and the occurrence times, and the second accumulation curve represents the relationship between the brightness values and the update appearance times; E) Perform a global mapping of the accumulated occurrences according to a dynamic range of the luminance values to generate a first output value, and perform a global mapping of the accumulated occurrences of the updated occurrences according to the dynamic range of the luminance values. Generating a second output value respectively; and (F) judging whether a current brightness value is less than a critical brightness value sequentially in each brightness value. If the current brightness value is less than the threshold brightness value, the corresponding first output value and the corresponding second output value are blended according to the threshold brightness value to generate a brightness output value. If the current brightness value is greater than or equal to the critical brightness value, the corresponding first output value is used as the brightness output value.

An embodiment of the present invention provides a contrast enhancement device based on histogram adjustment, and is used to enhance the contrast of an input image. Contrast enhancement device includes an image capturer With an image processor. The image capture device receives the input image and sequentially captures an input brightness value of each pixel position in the input image. The image processor is electrically connected to the image capture device and is used to perform the following steps: (A) receiving each input brightness value in the input image; (B) corresponding to a number of occurrences of each input brightness value on the histogram (C) enhance the number of occurrences corresponding to at least one luminance value that is less than a preset luminance value, and each luminance value corresponds to an updated occurrence number; (D) accumulate each occurrence number in order to generate A first accumulation curve and sequentially accumulating each update occurrence number to generate a second accumulation line, wherein the first accumulation curve represents the relationship between the brightness values and the occurrence times, and the second accumulation curve represents the brightness values and these Update the relationship of the number of occurrences; (E) Perform a global mapping of the accumulated occurrences according to a dynamic range of the luminance values to generate a first output value, respectively, and accumulate these accumulated values according to the dynamic range of the luminance values. Update the number of occurrences to perform global mapping to generate a second output value respectively; and (F) judge in each of the brightness values in sequence whether a current brightness value is less than one Luminance value. If the current brightness value is less than the threshold brightness value, the corresponding first output value and the corresponding second output value are blended according to the threshold brightness value to generate a brightness output value. If the current brightness value is greater than or equal to the critical brightness value, the corresponding first output value is used as the brightness output value.

In order to further understand the features and technical contents of the present invention, please refer to the following detailed description and accompanying drawings of the present invention, but these descriptions and attached drawings are only used to illustrate the present invention, not the right to the present invention No limitation on scope.

100‧‧‧ electronic device

110‧‧‧Image capture device

120‧‧‧Image Processor

Im‧‧‧ input image

P0-Pi‧‧‧Enter brightness value

OUT0-OUTi‧‧‧Output brightness value

S210, S220, S230, S240, S245, S250, S255, S260, S270, S280‧‧‧ steps

Hgram‧‧‧Histogram

Hgram1‧‧‧ Histogram

ADD1‧‧‧The first accumulation curve

ADD2‧‧‧Second Accumulation Curve

GM1‧‧‧first global mapping curve

GM2‧‧‧Second global mapping curve

GMout‧‧‧Output brightness curve

FIG. 1 is a schematic diagram of a contrast enhancement device based on histogram adjustment according to an embodiment of the present invention.

FIG. 2 is a flowchart of a contrast enhancement method based on histogram adjustment according to an embodiment of the present invention.

FIG. 3A is a histogram of the number of occurrences of an input brightness value according to an embodiment of the present invention Schematic illustration of statistics.

FIG. 3B is a schematic diagram of histogram statistics of the number of occurrences of update of the input brightness value according to an embodiment of the present invention.

FIG. 4A is a schematic diagram of a first accumulation curve according to an embodiment of the present invention.

FIG. 4B is a schematic diagram of a second accumulation curve according to an embodiment of the present invention.

FIG. 5A is a schematic diagram of a first global mapping curve according to an embodiment of the present invention.

FIG. 5B is a schematic diagram of a second global mapping curve according to an embodiment of the present invention.

FIG. 6 is a comparison diagram of a first global mapping curve and an output brightness curve according to an embodiment of the present invention.

Hereinafter, the present invention will be described in detail by illustrating various exemplary embodiments of the present invention with drawings. However, the inventive concepts may be implemented in many different forms and should not be construed as limited to the exemplary embodiments set forth herein. In addition, the same reference numerals may be used to indicate similar elements in the drawings.

Embodiments of the present invention provide a contrast enhancement method and device based on histogram adjustment, which perform histogram statistics on a single image and adjust statistics in the histogram. Furthermore, the contrast enhancement method and the contrast enhancement device enhance the number of occurrences of the dark area (ie, the lower brightness portion) in the histogram, and then perform a global mapping based on a critical brightness in the histogram to increase the dark portion. The brightness of the area is maintained and the brightness of the bright area (ie, the higher brightness portion) is maintained, and a brightness output value is generated accordingly. In this way, the contrast enhancement method and device based on histogram adjustment according to the embodiments of the present invention can avoid the occurrence of the conventional halo phenomenon, and can adjust the brightness of the dark area without affecting the brightness of the bright area, thereby achieving a comparative Best contrast enhancement. The method and device for contrast enhancement based on histogram adjustment disclosed in the present invention will be further described below.

First, please refer to FIG. 1, which shows a schematic diagram of a contrast enhancement device based on histogram adjustment according to an embodiment of the present invention. As shown in FIG. 1, the contrast enhancement device 100 It is used to enhance the contrast of an input image Im and output the adjusted output brightness values OUT0-OUTi. In this embodiment, the contrast enhancement device 100 may be a smart phone, a video recorder, a tablet computer, a notebook computer, or other contrast enhancement devices that need to adjust image contrast, which is not limited in the present invention.

The electronic device 100 includes an image capture device 110 and an image processor 120. As shown in FIG. 1, the image capture device 110 receives an input image Im and sequentially captures input brightness values P0-Pi at each pixel position (not shown in the figure) in the input image Im. Furthermore, the image capture unit 110 captures continuous images, and the input image Im is one of the continuous images.

The image processor 120 is electrically connected to the image capture unit 110 and is used to perform the following steps to adjust the input brightness value P0-Pi of each pixel position in the input image Im, thereby enhancing the contrast of the input image Im.

Please also refer to Figure 1-2. FIG. 2 shows a flowchart of a contrast enhancement method based on histogram adjustment according to an embodiment of the present invention. First, the image processor 120 receives each input brightness value P0-Pi in the input image Im to further analyze the characteristics of each input brightness value P0-Pi (step S210).

Next, the image processor 120 corresponds the number of occurrences of each input brightness value P0-Pi to a plurality of brightness values on the histogram (step S220). Furthermore, each input brightness value P0-Pi is represented by n bits. Therefore, these brightness values on the histogram will have a total of 2 nth power. For example, the input image Im has a total of 202 pixel positions (not shown in the figure). Each pixel position has an input brightness value, and the input brightness value of each pixel position is represented by a 4-bit value (that is, represented by 0-15). Therefore, these brightness values on the histogram will have a total of 2 to the 4th power, that is, 16 brightness values. The image processor 120 will count the number of occurrences of these input brightness values P0-Pi at 202 pixel positions, and correspond to the 16 brightness values 0-15 on the histogram.

As shown in FIG. 3A, the image processor 120 corresponds to the number of occurrences of these input luminance values P0-Pi at 202 pixel positions to the 16 luminances on the histogram Hgram Values are 0-15. For example, the luminance value 1 on the histogram Hgram corresponds to 10 occurrences, and a total of 10 occurrences of these input luminance values P0-Pi representing 202 pixel positions are 0. The image processor 120 also counts the number of occurrences corresponding to the brightness value 2-15 of the histogram Hgram in this way, so it will not be repeated here.

After performing the histogram statistics (ie, step S220), the image processor 120 will enhance the number of occurrences corresponding to at least one brightness value that is less than a preset brightness value, so as to reduce the dark area of the input image Im The dark part) is enhanced (step S230). At this time, each brightness value in the histogram will correspond to an updated update occurrence number. Furthermore, the image processor 120 enhances the number of occurrences corresponding to at least one luminance value smaller than a preset luminance value (for example, 3) to generate an enhanced number of occurrences corresponding to at least one luminance value. Next, the image processor 120 uses the number of occurrences of the enhancement occurrences and each luminance value equal to or greater than the preset luminance value as the update occurrences, so that each luminance value in the histogram will correspond to these update occurrences respectively. .

Following the example of FIG. 3A, as shown in FIG. 3B, the preset brightness value is set to 3. Therefore, the image processor 120 will enhance the number of occurrences corresponding to the brightness value less than 3 (ie, the brightness value 0-2) to generate the number of enhanced appearances corresponding to the brightness value 0-2. In this embodiment, the enhancement amplitude is 4 times. Therefore, the image processor 120 enhances the number of occurrences of the brightness value 0 (ie, 0 times), so that the corresponding number of enhancement appearances is 0 * 4 = 0 times. Similarly, the image processor 120 will enhance the number of occurrences of the brightness value 1 (ie, 10 times), so that the corresponding number of enhanced appearances is 10 * 4 = 40 times, and the image processor 120 will enhance the number of appearances of the brightness value 2 (ie, 12 times), so that the corresponding number of enhancement occurrences is 12 * 4 = 48 times. The value of the enhancement amplitude can also be designed according to the actual situation, which is not limited in the present invention.

Next, the image processor 120 further uses the number of occurrences corresponding to the above three enhancement appearances and each brightness value greater than or equal to 3 (that is, the brightness value 3-15) as the above-mentioned update appearances, so that each brightness in the histogram Hgram1 The values correspond to the number of times these updates occur. Through the above description, it can be organized into Equation 1, and Equation 1 As follows.

其中，i為目前的亮度值，ε為預設亮度值，a為增強幅度，H(i)為出現次數，且H'(i)為更新出現次數。因此，如圖3B所示，直方圖Hgram1中的亮度值1-15分別對應到的更新出現次數為40,48,22,30,11,10,9,8,7,5,11,13,9,15與30。據此，影像處理器120將增強小於3的亮度值對應的出現次數，以對輸入影像Im的暗部區域(即輸入影像Im中較暗的部分)進行增強。

Among them, i is the current brightness value, ε is the preset brightness value, a is the enhancement amplitude, H (i) is the number of occurrences, and H ′ (i) is the number of update occurrences. Therefore, as shown in FIG. 3B, the number of update occurrences corresponding to the brightness values 1-15 in the histogram Hgram1 is 40, 48, 22, 30, 11, 10, 9, 8, 7, 5, 11, 13, respectively. 9,15 and 30. According to this, the image processor 120 enhances the number of occurrences corresponding to the brightness value less than 3 to enhance the dark area of the input image Im (that is, the darker part of the input image Im).

After obtaining the number of occurrences corresponding to each brightness value and the number of corresponding update occurrences (step S230), the image processor 120 accumulates each occurrence number in order to generate a first accumulation curve (step S240). The first cumulative curve represents the relationship between these brightness values and the number of occurrences. In addition, the image processor 120 will sequentially accumulate each update occurrence number in order to generate a second accumulated line (step S250). The second cumulative curve represents the relationship between these brightness values and the number of occurrences of these updates.

Following the above example, please refer to FIGS. 3A and 4A at the same time. The image processor 120 will sequentially accumulate each occurrence number to generate a first accumulation curve ADD1, and the first accumulation curve A1 represents these brightness values 0-15 and these occurrence times. Relationship. For example, the number of cumulative appearances corresponding to brightness value 1 is 0 + 10 = 10; the number of cumulative appearances corresponding to brightness value 2 is 10 + 12 = 22; and the number of cumulative appearances corresponding to brightness value 3 is 22 + 22 = 44. The image processor 120 also calculates the accumulated number of occurrences corresponding to the brightness value 4-15 in the above manner, so it will not be repeated here.

Similarly, referring to FIGS. 3B and 4B at the same time, the image processor 120 will sequentially accumulate the number of occurrences of each update in order to generate a second accumulation curve ADD2, and the second accumulation curve ADD2 represents these brightness values 0-15 and these updates appear. The relationship of times. For example, the number of accumulated update occurrences corresponding to the brightness value 1 is 0 + 40 = 40; the number of cumulative update occurrences corresponding to the brightness value 2 is 40 + 48 = 88; and the number of cumulative update occurrences corresponding to the brightness value 3 is 88 + 22 = 110. The image processor 120 also calculates the number of cumulative update occurrences corresponding to the brightness value 4-15 in the above manner, so it will not be repeated here.

After step S240, the image processor 120 performs global mapping on the accumulated occurrences according to a dynamic range of the brightness values to generate a first output value (step S245). Furthermore, the image processor 120 normalizes the accumulated occurrence times to the dynamic range of the brightness values to generate the first output values, respectively. The brightness values and the corresponding first output values will form a first global mapping curve. In this embodiment, the dynamic range of the brightness value is 0-15. Therefore, the image processor 120 normalizes each accumulated appearance number to the dynamic range of the brightness value 0-15 to generate the first output values respectively.

Following the above example, please refer to FIG. 4A and FIG. 5A at the same time. It can be seen from FIG. 4A that the dynamic range of the brightness value is 0-15. There are 202 occurrences in total. The number of occurrences after accumulation corresponding to the brightness value 2 is taken as an example for illustration. The number of occurrences after the accumulation corresponding to the brightness value 2 is 22. Therefore, the image processor 120 normalizes the value 22 to the dynamic range of the brightness value 1-15 to correspond to the first output value T1 (i), which means that the first output value T1 (i) = 22 generated by the brightness value 2 * 15/202 = 1.63. If the image processor 120 unconditionally rounds off the first output value T1 (i), the first output value T1 (i) will be generated as 1.

Similarly, the accumulated number of occurrences corresponding to the brightness value 7 is 104. Therefore, the image processor 120 normalizes the value 104 to the dynamic range of the brightness value 1-15 to correspond to the first output value T1 (i), which means that the first output value T1 (i) = 104 * 15/202 = 7.72. Similarly, the image processor 120 unconditionally rounds off the first output value T1 (i) so that the first output value T1 (i) is 7. The image processor 120 also calculates the number of cumulative appearances corresponding to the brightness values 3-6 and 8-15 in the above manner to generate the first output value T1 (i) correspondingly, and displays it in Table 1 below. according to Therefore, the brightness value and the corresponding first output value T1 (i) will form a first global mapping curve GM1.

In addition, after step S250, the image processor 120 also performs global mapping on the accumulated occurrence times of updates according to the dynamic range of the brightness values to generate a second output value (step S255). Furthermore, the image processor 120 normalizes the accumulated occurrence times of the updates to the dynamic range of the brightness values to generate second output values, respectively. These brightness values and corresponding second output values will form a second global mapping curve. In this embodiment, the dynamic range of the brightness value is 0-15. Therefore, the image processor 120 normalizes the number of each update occurrence to the dynamic range of the brightness value 0-15 to generate the second output values respectively. .

Following the above example, please refer to FIG. 4B and FIG. 5B at the same time. It can be seen from FIG. 4B that the dynamic range of the brightness value is 0-15. There are 268 updates in total. Take the number of accumulated update occurrences corresponding to the brightness value 4 as an example for illustration. The number of accumulated updates corresponding to the brightness value 4 is 140. Therefore, the image processor 120 normalizes the value 96 to the dynamic range of the brightness value 1-15 to generate a second output value T2 (i) correspondingly, that is, the second output value T2 (i) = 140 * 15/268 = 7.83. If the image processor 120 unconditionally rounds off the second output value T2 (i), a second output value will be generated T2 (i) is 7. The image processor 120 also calculates the number of cumulative update occurrences corresponding to the brightness values 1-3 and 5-15 in the above manner to generate a second output value T2 (i) correspondingly, and is shown in Table 2 below. Accordingly, the brightness value and the corresponding second output value T2 (i) will form a second global mapping curve GM2.

After obtaining the first output value (step S245) and the second output value (step S255), the image processor 120 will sequentially determine in each brightness value whether a current brightness value is less than a critical brightness value (step S260), In the next steps S270 and S280, the first output value and the second output value are redistributed to increase the brightness of the dark area and maintain the brightness of the bright area.

Furthermore, the image processor 120 calculates the critical brightness value according to the brightness values and the corresponding number of occurrences, so as to determine where the critical brightness value falls among the brightness values. For example, referring to FIG. 3A at the same time, the image processor 120 adds up the result of multiplying each brightness value by the corresponding number of occurrences to generate a cumulative value, that is, the cumulative value = ((1 * 10) + (2 * 12 ) + (3 * 22) + (4 + 30) + (5 * 11) + (6 * 10) + (7 * 9) + (8 * 8) + (9 * 7) + (10 * 5) + (11 * 11) + (12 * 13) + (13 * 9) + (14 * 15) + (15 * 30)) = 1629. The image processor 120 then divides the accumulated value by the result of summing these occurrences to generate a critical brightness value, that is, a critical brightness value = 1629 / (10 + 12 + 22 + 30 + 11 + 10 + 9 + 8 + 7 + 5 + 11 + 13 + 9 + 15 + 30) = 8.064. The image processor 120 will unconditionally cut off the critical brightness value so that the critical brightness value is 8.

Through the above example, it can be summarized into Equation 2, and Equation 2 is shown below.

其中，i為目前的亮度值，H(i)為出現次數，Σ(i*H(i))為累計值，且δ為臨界亮度值。而上述臨界亮度值亦可以根據實際狀況而使用其他計算方式，本發明對此不作限制。

Among them, i is the current brightness value, H (i) is the number of occurrences, Σ (i * H (i)) is the cumulative value, and δ is the critical brightness value. The above-mentioned critical brightness value may also be calculated in other ways according to actual conditions, which is not limited in the present invention.

Therefore, in step S260, the image processor 120 will sequentially determine whether the current brightness value is less than the threshold brightness value in each brightness value, so as to redistribute the first output value and the second output value according to the threshold brightness value, and then adjust The brightness of the high dark area is maintained and the brightness of the bright area is maintained.

Please refer to FIGS. 5A and 5B at the same time. If the current brightness value is less than the critical brightness value, it means that the current brightness value belongs to the dark area and needs to be enhanced. At this time, the image processor 120 blends the corresponding first output value and the corresponding second output value according to the threshold brightness value to generate a brightness output value (step S270). In this embodiment, the image processor 120 calculates a first weight ratio and a second weight ratio according to the current brightness value and the critical brightness value, and the sum of the first weight ratio and the second weight ratio is 1. Furthermore, the image processor 120 mixes the first output value of the first weight ratio and the second output value of the second weight ratio to generate a brightness output value corresponding to the current brightness value.

Following the above example, the critical brightness value is 8 and the current brightness value is 2 for description. As shown in FIGS. 5A-5B, the image processor 120 will determine that the current brightness value (ie, 2) is less than the critical brightness value (ie, 8). At this time, the image processor 120 divides the current brightness value by the threshold brightness value to generate a first weight ratio, that is, the first weight ratio = 2/8. Then, the image processor 120 subtracts 1 from the first weight ratio to generate a second weight ratio, that is, the second weight ratio = 1-2 / 8 = 6/8. Again, the image processor 120 Mix the first output value of the first weight ratio with the second output value of the second weight ratio to generate the brightness output value corresponding to the current brightness value, that is, the brightness output value = (2/8) * 1 + (6/8) * 4 = 3.25. The image processor 120 unconditionally rounds down the brightness output value so that the brightness output value is 3.

In the process of the image processor 120 sequentially determining whether the current brightness value is less than the critical brightness value, if the current brightness value is greater than or equal to the critical brightness value, it means that the current brightness value belongs to the bright area and does not need to be enhanced. At this time, the image processor 120 uses the first output value corresponding to the current brightness value as the brightness output value (step S280).

Following the above example, the critical brightness value is 8 and the current brightness value is 13 for explanation. As shown in FIGS. 5A-5B, the image processor 120 will determine that the current brightness value (ie, 13) is greater than or equal to the critical brightness value (ie, 8). At this time, the image processor 120 uses the first output value corresponding to the current brightness value as the brightness output value, that is, the brightness output value = 11.

The above example of the brightness output value shows that it can be sorted into Equation 3, and Equation 3 is shown below.

其中，i為目前的亮度值，δ為臨界亮度值，A(i)為第一權重比例，T1(i)為第一輸出值，B(i)為第二權重比例，T2(i)為第二輸出值，且OUT(i)為亮度輸出值。而上述亮度輸出值亦可以根據實際狀況而使用其他計算方式，本發明對此不作限制。

Among them, i is the current brightness value, δ is the critical brightness value, A (i) is the first weight ratio, T1 (i) is the first output value, B (i) is the second weight ratio, and T2 (i) is The second output value, and OUT (i) is a luminance output value. The above-mentioned brightness output value may also use other calculation methods according to actual conditions, which is not limited in the present invention.

Following the above example, the image processor 120 calculates a brightness output value OUT (i) corresponding to each brightness value according to Formula 3, and displays the brightness output value OUT (i) in Table 3 below. According to this, the image processor 120 will sequentially calculate the corresponding brightness output value OUT (i) in each brightness value to form an output brightness curve GMout, as shown in FIG. 6.

FIG. 6 is a comparison diagram of the first global mapping curve GM1 and the output brightness curve GMout. Therefore, among the current brightness values 1-7, the brightness output value of the output brightness curve GMout will be higher than the brightness output value of the first global mapping curve GM1 (that is, the brightness of the dark area is increased). In the current brightness value 8-15, the brightness output value of the output brightness curve GMout will be equal to the brightness output value of the first global mapping curve GM1 (that is, the brightness of the bright area is maintained).

In summary, a contrast enhancement method and device based on histogram adjustment provided in the embodiment of the present invention, which enhances the number of occurrences corresponding to the dark area (ie, the lower brightness part) in the histogram, and then according to the histogram The critical brightness in the global mapping is performed to increase the brightness of the dark area and maintain the brightness of the bright area (ie, the higher brightness part), and generate a brightness output value (ie, the output brightness curve) corresponding to each brightness value accordingly. In this way, the contrast enhancement method and device based on histogram adjustment according to the embodiments of the present invention can avoid the occurrence of the conventional halo phenomenon, and can adjust the brightness of the dark area without affecting the brightness of the bright area, thereby achieving a comparative Best contrast enhancement.

The above description is only an embodiment of the present invention, and is not intended to limit the patent scope of the present invention.

Claims (10)

A contrast enhancement method based on histogram adjustment is suitable for a contrast enhancement device to enhance the contrast of an input image, and the contrast enhancement method includes: receiving an input brightness value of each pixel position in the input image; A number of occurrences of the input luminance value corresponds to a plurality of luminance values on the histogram; the number of occurrences corresponding to the at least one luminance value less than a preset luminance value is enhanced, and each luminance value corresponds to an update The number of occurrences; each of the occurrences is sequentially accumulated to generate a first accumulation curve, and each of the update occurrences is sequentially accumulated to produce a second accumulation line, wherein the first accumulation curve represents the brightness values and the Relationship between the number of occurrences, and the second accumulation curve represents the relationship between the brightness values and the number of update appearances; according to a dynamic range of the brightness values, a global mapping is performed on the accumulated occurrences to generate separately A first output value, and performing global mapping on the accumulated update times based on the dynamic range of the brightness values to divide Generating a second output value; and sequentially determining in each of the brightness values whether a current brightness value is less than a critical brightness value, and if the current brightness value is less than the critical brightness value, blending corresponding according to the critical brightness value The first output value and the corresponding second output value to generate a brightness output value, and if the current brightness value is greater than or equal to the critical brightness value, the corresponding first output value is used as the brightness output value. For example, the contrast enhancement method based on histogram adjustment of claim 1, wherein the step of enhancing the number of occurrences corresponding to the at least one brightness value smaller than the preset brightness value further includes: The number of occurrences corresponding to the at least one luminance value to generate an enhanced number of occurrences corresponding to the at least one luminance value; and the number of occurrences corresponding to each of the luminance values greater than or equal to the preset luminance value The number of occurrences of the updates is corresponding to the brightness values. For example, the contrast enhancement method based on histogram adjustment of claim 1, wherein the step of performing global mapping on the accumulated occurrences further includes: normalizing the accumulated occurrences to the brightness The dynamic ranges of the values are used to generate the first output values respectively, and the brightness values and the corresponding first output values form a first global mapping curve. For example, the contrast enhancement method based on histogram adjustment of claim 1, wherein the step of performing the global mapping on the accumulated occurrence times of the updates further includes normalizing the accumulated occurrence times of the updates to The dynamic ranges of the brightness values are used to generate the second output values respectively, and the brightness values and the corresponding second output values form a second global mapping curve. For example, the histogram-based contrast enhancement method of claim 1, wherein in the step of determining whether the current brightness value is less than the critical brightness value, the method further includes: calculating the threshold according to the brightness values and the corresponding number of occurrences. Brightness value. For example, the histogram-based contrast enhancement method of claim 5, wherein in the step of calculating the critical brightness value, the method further comprises: adding up a result of multiplying each brightness value by a corresponding number of occurrences to generate a cumulative A value; and a result of dividing the accumulated value by adding the occurrences to generate the critical brightness value. For example, the histogram-based contrast enhancement method of claim 1, wherein the step of mixing the corresponding first output value and the corresponding second output value further includes: according to the current brightness value and the critical brightness value Calculating a first weight ratio and a second weight ratio, and a sum of the first weight ratio and the second weight ratio is 1; and mixing the first output value of the first weight ratio with the second weight ratio The second output value is used to generate the brightness output value corresponding to the current brightness value. For example, the contrast enhancement method based on histogram adjustment of claim 7, wherein in the step of calculating the first weight ratio and the second weight ratio, the method further includes: dividing the current brightness value by the critical brightness value to generate the A first weighting ratio; and subtracting the first weighting ratio from 1 to produce the second weighting ratio. A contrast enhancement device based on histogram adjustment is used to enhance the contrast of an input image, and the contrast enhancement device includes: an image capturer, receiving the input image, and sequentially capturing each pixel position in the input image An input brightness value; and an image processor, which is electrically connected to the image capture device, and is used to perform the following steps: receiving each of the input brightness values in the input image; and generating one occurrence of each of the input brightness values. The number of times corresponds to a plurality of brightness values on the histogram; the number of occurrences corresponding to the at least one brightness value that is less than a preset brightness value is enhanced, and each of the brightness values corresponds to an updated number of occurrences; each is sequentially accumulated The number of occurrences generates a first accumulation curve, and each of the update occurrences is sequentially accumulated to generate a second accumulation line, wherein the first accumulation curve represents a relationship between the brightness values and the occurrences, and the The second accumulation curve represents the relationship between the brightness values and the number of occurrences of the updates; the accumulated times are counted according to a dynamic range of the brightness values. A global mapping to generate a first output value separately, and performing the global mapping on the accumulated update occurrences according to the dynamic range of the luminance values to generate a second output value separately; and sequentially to each The brightness value determines whether a current brightness value is less than a critical brightness value. If the current brightness value is less than the critical brightness value, the corresponding first output value and the corresponding second output are blended according to the critical brightness value. Value to generate a brightness output value, and if the current brightness value is greater than or equal to the critical brightness value, the corresponding first output value is used as the brightness output value. For example, the histogram-based contrast enhancement device according to claim 9, wherein each of the input brightness values is represented by n bits, and the brightness values on the histogram are 2 to the power of n.