Image magnification method, image magnification device, image processing chip and display equipment

Abstract

The invention discloses an image magnification method, an image magnification device, an image processing chip and display equipment. The method comprises the following steps: receiving an original image; carrying out edge detection on the original image and calculating a pixel value difference value in the original image; judging whether the pixel value difference value is greater than a preset threshold value or not; when the pixel value difference value is greater than a preset threshold value, amplifying the original image by adopting a first interpolation method; and when the pixel value difference value is not greater than a preset threshold value, amplifying the original image by adopting a second interpolation method. According to the image magnification method, the image magnification device, the image processing chip and the display equipment provided by the invention, the edge part of the image is detected, and different magnification algorithms are selected according to the pixel value difference, so that the display effect of a color image is reserved, and the sharpness of images such as an image engineering drawing and fonts after magnification is enhanced.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to an image magnification method, an image magnification device, an image processing chip, and a display device. Background Technology

[0002] The purpose of image magnification is to increase the resolution of the magnified image to meet people's visual requirements or practical application requirements. Image magnification has very important applications in fields such as high-definition television and medical imaging.

[0003] Currently, the same algorithm is commonly used to enlarge images. Bilinear interpolation is the most commonly used image enlargement algorithm, with nearest neighbor search algorithm and cubic convolution interpolation being widely adopted. Bilinear interpolation is relatively complex. While it avoids pixel value discontinuities and produces high-quality enlarged images, it acts as a low-pass filter, which can impair high-frequency components. Therefore, it may blur the edges and details of various subjects in the image to some extent.

[0004] Bilinear Upscaling is an image upscaling algorithm used to enlarge low-resolution images to high-resolution ones. It's based on the principle of bilinear interpolation, generating new pixel values ​​by interpolating between pixels. Specifically, the algorithm determines the value of a new pixel by calculating the weighted average of the four nearest neighbors of the target pixel. This weighted average is calculated based on the distance between the target pixel and its nearest neighbors, with closer pixels having higher weights. This algorithm is relatively simple and computationally efficient, but it may cause some blurring and distortion issues.

[0005] In addition, when enlarging an image, it can cause over-display areas to appear at the edges, which reduces the sharpness of the image. Summary of the Invention

[0006] In view of the above problems, the purpose of this invention is to provide an image magnification method, an image magnification device, an image processing chip, and a display device. By detecting the edge parts of the image and selecting different magnification algorithms according to the pixel value difference, not only is the display effect of the color image preserved, but the sharpness of magnified images such as engineering drawings and fonts is also enhanced.

[0007] According to one aspect of the present invention, an image magnification method is provided, comprising: receiving an original image; performing edge detection on the original image and calculating pixel value differences in the original image; determining whether the pixel value differences are greater than a preset threshold; when the pixel value differences are greater than the preset threshold, magnifying the original image using a first interpolation method; and when the pixel value differences are not greater than the preset threshold, magnifying the original image using a second interpolation method.

[0008] Optionally, between the steps of receiving the original image and performing edge detection on the original image and calculating the pixel value difference in the original image, the method further includes: calculating the magnification ratio of the original image based on the size of the original image and the target image, wherein the magnification ratio includes a horizontal magnification ratio and a vertical magnification ratio, and the target image is the magnified original image.

[0009] Optionally, the pixel value difference is the absolute value of the difference between the pixel values ​​of two adjacent pixels in the original image.

[0010] Optionally, if a target pixel has multiple adjacent pixels, then in the step of determining whether the pixel value difference is greater than a preset threshold, it is necessary to sequentially determine the size of the pixel value difference between the target pixel and the multiple adjacent pixels and the preset threshold.

[0011] Optionally, when it is necessary to determine the difference between the pixel values ​​of multiple adjacent pixels and the target pixel and the preset threshold, if the difference between the pixel values ​​of one of the adjacent pixels and the target pixel is greater than the preset threshold, the original image is magnified using the first interpolation method.

[0012] Optionally, the original image is a complete image or a portion of a complete image.

[0013] Optionally, the pixel value difference is the pixel value difference of the edge portion detected in the edge detection step.

[0014] Optionally, the first interpolation method includes a nearest neighbor interpolation algorithm, and the second interpolation method includes a bilinear interpolation algorithm.

[0015] According to another aspect of the present invention, an image magnification device is provided, comprising: a data receiving module for receiving data of an original image; an edge detection module connected to the data receiving module for performing edge detection and pixel value difference calculation on the original image; a scaling factor determination module connected to the data receiving module for determining a scaling factor based on the size of the original image and the size of a target image; and an image magnification module connected to the edge detection module and the scaling factor determination module for determining the relationship between the pixel value difference and a preset threshold, and selecting a first interpolation method or a second interpolation method to magnify the original image based on the comparison result.

[0016] According to another aspect of the present invention, an image processing chip is provided, including the image magnification device as described in claim 8.

[0017] According to another aspect of the present invention, a display device is provided, including the image magnification device as described in claim 8.

[0018] The image magnification method, image magnification device, image processing chip, and display device provided in this application, during the magnification of a received image, detect the pixel value difference of the image's edge regions and then select different image magnification methods. When the pixel value difference is no greater than a preset threshold, a bilinear interpolation algorithm is used to magnify the image to maintain a smooth gradient; when the pixel value difference is greater than the preset threshold, a nearest neighbor interpolation algorithm is used to magnify the image to maintain the sharpness of the image edges. Therefore, when magnifying different images, not only is the display effect of color images preserved, but the sharpness of magnified images such as engineering drawings and fonts is also enhanced.

[0019] Furthermore, the image magnification method, image magnification device, image processing chip, and display device provided in this application do not require color coordinate space conversion or frequency domain numerical processing during image magnification, enabling real-time and rapid image magnification. In addition, because real-time processing is possible during image magnification—that is, the original image data can be magnified immediately upon receipt—it can be used with interfaces that do not use SRAM.

[0020] Furthermore, the image magnification method, image magnification device, image processing chip, and display device provided in this application can magnify the original image that needs to be magnified, whether it is the entire image or a part of the entire image, quickly, instantly, and with high display effect. Attached Figure Description

[0021] The above and other objects, features and advantages of the present invention will become more apparent from the following description of embodiments of the invention with reference to the accompanying drawings, in which:

[0022] Figure 1a A flowchart of an image magnification method according to the prior art is shown;

[0023] Figure 1b A schematic diagram illustrating image magnification according to existing technology is shown;

[0024] Figure 2 A schematic diagram of the structure of an image magnification device according to an embodiment of the present invention is shown;

[0025] Figure 3 A flowchart of an image magnification method according to an embodiment of the present invention is shown;

[0026] Figure 4a and Figure 4b A schematic diagram of two algorithms in an image magnification method according to an embodiment of the present invention is shown;

[0027] Figure 5 A schematic diagram illustrating the image magnification effect according to an embodiment of the present invention is shown. Detailed Implementation

[0028] Various embodiments of the invention will now be described in more detail with reference to the accompanying drawings. In the various drawings, the same elements are indicated by the same or similar reference numerals. For clarity, the various parts in the drawings are not drawn to scale.

[0029] Figure 1a A flowchart of an image magnification method according to the prior art is shown; Figure 1b A schematic diagram illustrating the enlargement of an image according to existing technology is shown.

[0030] refer to Figure 1a In existing real-time image magnification methods, bilinear interpolation algorithms are typically used to magnify the image. That is, after receiving the image data, the display device magnifies the image using bilinear interpolation and can then display it without any other operations or storage of the image data.

[0031] Bilinear interpolation, by using the values ​​and positions of nearest-neighbor pixels, can maintain smooth edges when enlarging an image. However, it also has some limitations; for example, in areas with large grayscale variations, the enlarged image may show transition regions, such as... Figure 1b As shown, this may cause the image to become blurry or distorted, and it can also easily reduce the sharpness of the image, especially if it affects engineering drawings or fonts.

[0032] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples.

[0033] Figure 2A schematic diagram of the structure of an image magnification device according to an embodiment of the present invention is shown; Figure 3 A flowchart of an image magnification method according to an embodiment of the present invention is shown; Figure 4a and Figure 4b A schematic diagram of two algorithms in an image magnification method according to an embodiment of the present invention is shown; Figure 5 A schematic diagram illustrating the image magnification effect according to an embodiment of the present invention is shown.

[0034] refer to Figure 2 The image magnification device 100 of this application includes: a data receiving module 110, an edge detection module 120, a ratio determination module 130, and an image magnification module 140.

[0035] The data receiving module 110 receives the data of the original image, which can be all the data of a complete image or a portion of a complete image. The edge detection module 120 is connected to the data receiving module 110 and is used to identify edges or contours in the image. The edge detection module 120 calculates the pixel values ​​of the original image, especially the pixel values ​​of the edge parts with large color or brightness changes, and calculates the pixel value difference corresponding to the area where the pixel value changes significantly, to confirm the edges or contours in the original image. The scale determination module 130 is connected to the data receiving module 110 and is used to obtain the original image size and calculate the ratio between the original image size and the target image size to determine the magnification ratio of the original image. The image magnification module 140 is connected to the edge detection module 120 and the scale determination module 130 and is used to determine the relationship between the pixel value difference and the preset threshold, select different image magnification algorithms based on the comparison results, and magnify the image according to the magnification ratio calculated by the scale determination module 130.

[0036] In this embodiment, the edge detection module 120 acquires pixel values ​​of the original image, which represent, for example, the brightness or color of the image. Each pixel has a value representing the intensity of its brightness or color, and these values ​​can be used to construct the image. In a grayscale image, the pixel value represents the intensity of brightness, typically ranging from 0 to 255, where 0 represents black and 255 represents white. In a color image, the pixel value of each pixel consists of values ​​from the red, green, and blue channels, also typically ranging from 0 to 255, used to represent the color intensity of the pixel.

[0037] In this embodiment, the edge detection module 120 employs an edge detection algorithm, which is a technique used to identify edges or contours in an image. Edges are areas in an image with significant changes in grayscale or color, typically representing boundaries between objects or texture variations within an object.

[0038] Edge detection algorithms determine the location of edges by analyzing the grayscale or color differences (i.e., pixel values) of pixels in an image. Commonly used edge detection algorithms include Sobel, Prewitt, and Canny. These algorithms typically determine the location of edges by calculating the gradient (intensity and direction of grayscale or color changes) of pixel values ​​in the image.

[0039] In image magnification, edge detection can be used to extract edge information from an image, preserving edge sharpness and detail during the magnification process. By identifying edges, the structure and shape of the image can be better maintained, avoiding blurring or distortion after magnification.

[0040] The magnification ratio calculated by the scaling module 130 includes both horizontal and vertical magnification ratios. Furthermore, in determining the magnification ratio of the original image, the final target image size is known, or in other words, the target image size is fixed for a given display device. Therefore, the scaling module 130 only needs to obtain the size of the original image to calculate its horizontal and vertical magnification ratios.

[0041] Furthermore, the image magnification module 140 employs a first interpolation method or a second interpolation method to magnify the original image. The first interpolation method includes, for example, a nearest neighbor interpolation algorithm, and the second interpolation method includes, for example, a bilinear interpolation algorithm. Specifically, different image magnification algorithms are selected based on a comparison between the pixel value difference and a preset threshold. When the pixel value difference is not greater than the preset threshold, the bilinear interpolation algorithm is used for image magnification; when the pixel value difference is greater than the preset threshold, the nearest neighbor interpolation algorithm is used for image magnification.

[0042] Bilinear interpolation, by using the values ​​and positions of nearest-neighbor pixels, can maintain the smoothness of edges when enlarging an image; while nearest-neighbor interpolation, by finding the data point closest to a given query point in a given dataset, can maintain the sharpness of edges when enlarging an image. Therefore, the image enlargement module 140 enlarges the image by selecting different algorithms for different edge detection methods, so that the enlarged image not only maintains the smooth transition display effect of the original color image, but also improves the sharpness of images that affect engineering drawings or fonts, thereby improving the display effect.

[0043] Furthermore, Figure 3 A flowchart of the image magnification method of this application is shown, and its steps are as follows:

[0044] Step S101: Receive the original image data and perform pixel value detection and image magnification ratio confirmation on the original image.

[0045] In this step, the data receiving module 110 receives the data of the original image to be displayed, and then the edge detection module 120 detects the pixel value of each pixel in the original image. For grayscale images, the pixel value is, for example, the brightness of each pixel, while for color images, the pixel value is, for example, the color intensity of the three channels: red, green, and blue. The scaling module 130 calculates the size of the original image and calculates the horizontal and vertical scaling ratios based on the size of the target image.

[0046] In this embodiment, the horizontal / vertical magnification ratio is obtained, for example, by dividing the horizontal / vertical dimensions of the target image by the horizontal / vertical dimensions of the original image. Furthermore, calculating the magnification ratio of the original image also helps in calculating the position of each pixel in the original image within the target image.

[0047] Furthermore, for a given display device, since the size of the display panel of the display device is fixed, the size of the target image of the display device is also fixed, which makes it easy to calculate the horizontal and vertical magnification ratios of the original image.

[0048] Step S102: Calculate the pixel value difference in the original image.

[0049] In this step, the edge detection module 120 obtains the regions in the image with large changes in pixel values ​​through the edge detection algorithm, and calculates the pixel value difference in the region.

[0050] In one example of image magnification, the same pixel value difference will result in different magnification effects depending on the algorithm used. For example, bilinear interpolation can maintain the smoothness of image edges, while nearest neighbor interpolation can improve the sharpness of image edges. Therefore, choosing a suitable algorithm can improve the display effect of the magnified image.

[0051] Step S103: Determine whether the pixel value difference is greater than a preset threshold.

[0052] In this step, the relationship between the pixel value difference and the preset threshold is determined. When the pixel value difference is greater than the preset threshold, step S105 is executed; when the pixel value difference is not greater than the preset threshold, step S104 is executed.

[0053] Specifically, for example in one embodiment, referencing Figure 4aImage magnification is performed using a bilinear interpolation algorithm. The original image contains four pixels A, B, C, and D. After magnification by a factor of two, the newly added pixel A' coincides with the position of pixel A, and its pixel value is the same as that of pixel A. The newly added pixel B' is located between pixels A and B, and its pixel value is the average of (A+B). The newly added pixel C' is located between pixels A and C, and its pixel value is the average of (A+C). The newly added pixel D' is located between pixels A and D, and its pixel value is the average of (A+B+C+D).

[0054] Further, refer to Figure 4b When using the nearest neighbor interpolation algorithm to enlarge an image, the pixel value of a newly added pixel is taken from the pixel value of the four pixels A, B, C, and D that is closest to it. For example, D' is closest to point D, so the pixel value of D' is the pixel value of point D.

[0055] In this embodiment, if a target pixel has multiple adjacent pixels, then in the step of determining whether the pixel value difference is greater than a preset threshold, it is necessary to sequentially determine the difference between the pixel values ​​of the multiple adjacent pixels and the target pixel and the preset threshold. The target pixel is, for example, a pixel in the magnified target image.

[0056] Specifically, in this step, for example, in the process of calculating which algorithm should be used for the pixel value of point B', the step of determining whether the pixel value difference is greater than a preset threshold includes: first, calculating the difference between the pixel values ​​of points A and B, and then determining whether the pixel value difference (|AB|) is greater than the preset threshold; if determining the algorithm that should be used for point C', then determining whether the pixel value difference (|AC|) is greater than the preset threshold; if determining the algorithm that should be used for point D', then determining whether at least one of the pixel value differences (|AB|), (|AC|), and (|AD|) is greater than the preset threshold.

[0057] Step S104: Enlarge the image using the second interpolation method.

[0058] In this step, since the pixel value difference is not greater than the preset threshold, the image in this area is considered to be a gradient part, and it is more suitable to use the second interpolation method, namely the bilinear interpolation algorithm, so that the smooth gradient of the image can still be maintained in the magnified image, thereby improving the display effect.

[0059] Specifically, the bilinear upscaling algorithm is a commonly used image upscaling algorithm. (See reference...) Figure 4aThe principle and steps are as follows: 1. Input a low-resolution image that needs to be enlarged to the target resolution. 2. Calculate the size ratio between the target image and the original image to determine the magnification factor. 3. Traverse each pixel of the target image and calculate its position in the original image. 4. For each target pixel, find its four nearest neighbor pixels in the original image. 5. Based on the values ​​and positions of the nearest neighbor pixels, use bilinear interpolation to calculate the value of the target pixel; this includes: first, interpolating the nearest neighbor pixels horizontally to obtain two temporary pixel values; then, interpolating the two temporary pixel values ​​vertically to obtain the final target pixel value. 6. Assign the calculated target pixel value to the corresponding position in the target image. 7. Repeat steps 3-6 until all pixels of the target image have been traversed. 8. Output the enlarged image.

[0060] Step S105: Enlarge the image using the first interpolation method.

[0061] In this step, since the pixel value difference is greater than the preset threshold, the image in this area is considered to be a part of abrupt change, and it is more suitable to use the first interpolation method, namely the nearest neighbor interpolation algorithm, so that the image sharpness can still be maintained in the magnified image, thereby improving the display effect.

[0062] Among them, the nearest neighbor search algorithm is a method for finding the nearest neighbor. (See reference...) Figure 4b The principle and steps of image magnification are as follows: 1. Input the original image and magnification factor. Assume the size of the original image is M x N, and the magnification factor is k. 2. Calculate the size of the magnified image. Multiply the width and height of the original image by the magnification factor k, respectively, to obtain the width of the magnified image as M' = M * k and the height as N' = N * k. 3. Create a blank canvas for the magnified image. Based on the size of the magnified image, create a blank canvas of M' x N'. 4. For each pixel in the magnified image, find the nearest pixel in the original image. For each pixel (i', j') in the magnified image, calculate the corresponding position (i, j) in the original image. This can be obtained by dividing (i', j') by the magnification factor k and taking the integer part. 5. Copy the pixel value from the original image to the corresponding position in the magnified image. Copy the pixel value at position (i, j) in the original image to the pixel value at position (i', j') in the magnified image. 6. Repeat steps 4 and 5 until all pixels in the enlarged image have been assigned a value. 7. Output the enlarged image. Use the enlarged image as the output.

[0063] In this embodiment, for example, refer to Figure 4bWhen determining the algorithm used by D', if any of the pixel value differences (|AB|), (|AC|), and (|AD|) is greater than a preset threshold, then the nearest neighbor interpolation algorithm is used.

[0064] refer to Figure 5 As can be seen, the image magnification method of this application determines the image magnification algorithm based on the pixel value difference. Therefore, for images with color gradients, the magnification can still maintain a smooth gradient, and for images with abrupt changes, the magnification can also maintain the sharpness of the edges, thus improving the display effect.

[0065] This application also provides an image processing chip, including the image magnification device described above.

[0066] This application also provides a display device, including the image magnification device described above. Furthermore, the display device may also include, for example, an organic light-emitting diode (OLED), a liquid crystal display (LCD), or a touch and display driver integration (TDDI).

[0067] The image magnification method, image magnification device, image processing chip, and display device provided in this application, during the magnification of a received image, detect the pixel value difference of the image's edge regions and then select different image magnification methods. When the pixel value difference is no greater than a preset threshold, a bilinear interpolation algorithm is used to magnify the image to maintain a smooth gradient; when the pixel value difference is greater than the preset threshold, a nearest neighbor interpolation algorithm is used to magnify the image to maintain the sharpness of the image edges. Therefore, when magnifying different images, not only is the display effect of color images preserved, but the sharpness of magnified images such as engineering drawings and fonts is also enhanced.

[0068] Furthermore, the image magnification method, image magnification apparatus, image processing chip, and display device provided in this application do not require color coordinate space conversion or frequency domain numerical processing during image magnification, enabling real-time and rapid image magnification. In addition, because real-time processing is possible during image magnification—that is, the original image data can be magnified immediately upon receipt—it can be used with interfaces that do not utilize memory.

[0069] Furthermore, the image magnification method, image magnification device, image processing chip, and display device provided in this application can magnify the original image that needs to be magnified, whether it is the entire image or a part of the entire image, quickly, instantly, and with high display effect.

[0070] As described above, these embodiments of the present invention do not exhaustively cover all details, nor do they limit the invention to the specific embodiments described. Clearly, many modifications and variations can be made based on the above description. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to effectively utilize the invention and its modifications. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. An image magnification method, characterized in that, include: Receive the raw image; Edge detection is performed on the original image and the pixel value difference in the original image is calculated; Determine whether the difference in pixel values ​​is greater than a preset threshold; When the difference in pixel values ​​is greater than a preset threshold, the original image is enlarged using a first interpolation method; When the difference in pixel values ​​is not greater than a preset threshold, the original image is magnified using a second interpolation method.

2. The image magnification method according to claim 1, characterized in that, Between the steps of receiving the original image and performing edge detection on the original image and calculating the pixel value difference in the original image, the method further includes: The magnification ratio of the original image is calculated based on the sizes of the original image and the target image. The magnification ratio includes a horizontal magnification ratio and a vertical magnification ratio, and the target image is the magnified original image.

3. The image magnification method according to claim 1, characterized in that, The pixel value difference is the absolute value of the difference between the pixel values ​​of two adjacent pixels in the original image.

4. The image magnification method according to claim 3, characterized in that, If a target pixel has multiple adjacent pixels, then in the step of determining whether the difference in pixel values ​​is greater than a preset threshold, it is necessary to sequentially determine the difference in pixel values ​​between the target pixel and the multiple adjacent pixels and the preset threshold.

5. The image magnification method according to claim 4, characterized in that, When it is necessary to determine the difference between the pixel values ​​of multiple adjacent pixels and the target pixel and the preset threshold, if the difference between the pixel values ​​of one of the adjacent pixels and the target pixel is greater than the preset threshold, the original image is magnified using the first interpolation method.

6. The image magnification method according to claim 1, characterized in that, The original image is either a complete image or a portion of a complete image.

7. The image magnification method according to claim 1, characterized in that, The pixel value difference is the pixel value difference of the edge portion detected in the edge detection step.

8. The image magnification method according to claim 1, characterized in that, The first interpolation method includes the nearest neighbor interpolation algorithm, and the second interpolation method includes the bilinear interpolation algorithm.

9. An image magnification apparatus for performing the image magnification method as described in any one of claims 1-8, characterized in that, The image magnification device includes: The data receiving module is used to receive data from the original image; An edge detection module, connected to the data receiving module, is used to perform edge detection and pixel value difference calculation on the original image; A scaling ratio determination module, connected to the data receiving module, is used to determine the magnification ratio based on the size of the original image and the size of the target image. The image magnification module, connected to the edge detection module and the ratio determination module, is used to determine the relationship between the pixel value difference and a preset threshold, and select a first interpolation method or a second interpolation method to magnify the original image based on the comparison result.

10. An image processing chip, characterized in that, Includes the image magnification device as described in claim 9.

11. A display device, characterized in that, Includes the image magnification device as described in claim 9.

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