Image blur processing method, device, equipment, and computer-readable storage medium

Abstract

The present application proposes a method, device, equipment, and computer-readable storage medium for image blur processing, including: determining an image to be blurred, wherein the image to be blurred includes data information; dividing the image to be blurred into at least two regions according to changes in the data information in the image to be blurred, wherein the regions obtained after division include data information; detecting a region where the data information has changed, and performing a blur update process on the region where the data information has changed; merging the region after the blur update process with the remaining region in the image to be blurred that has not been blurred and updated, to obtain a blur update map. The image blur processing method can achieve a better highlighting effect; and while achieving a blur effect, the operation speed can be improved by partition blurring.

Description

Technical Field

[0001] The present application relates to an image processing method, and more particularly to an image blur processing method, apparatus, device, and computer-readable storage medium. Background Art

[0002] The human-machine interface (HMI) is the medium for interaction and information exchange between the system and the user. It realizes the conversion between the internal form of information and the form acceptable to humans. When the background image is dynamically simulated, the entire global background image is processed, which makes the system operation cost higher. Summary of the invention

[0003] The embodiments of the present application provide a method, device, equipment, and computer-readable storage medium for image blur processing to solve the problems existing in the related technologies. The technical solutions are as follows:

[0004] In a first aspect, an embodiment of the present application provides a method for image blur processing, comprising:

[0005] Determining a picture to be blurred, wherein the picture to be blurred includes data information;

[0006] Dividing the image to be blurred into at least two regions according to the change of the data information in the image to be blurred, wherein the regions obtained after the division contain data information;

[0007] Detecting that there is an area where the data information has changed, and performing fuzzy update processing on the area where the data information has changed;

[0008] The area after the blur update processing is merged with the remaining area of ​​the image to be blurred that has not been blurred and updated to obtain a blur update image.

[0009] In a second aspect, the embodiment of the present application further provides a device for image blur processing, comprising:

[0010] A first picture determination module, used to determine a picture to be blurred, wherein the picture to be blurred includes data information;

[0011] A partitioning module, used for dividing the image to be blurred into at least two areas according to the change of the data information in the image to be blurred, wherein the areas obtained after the division contain data information;

[0012] An image processing module is used to detect the area where the data information has changed, and perform fuzzy update processing on the area where the data information has changed;

[0013] The image merging module is used to merge the area after the blurring update processing with the remaining area of ​​the image to be blurred that has not been blurred and updated, so as to obtain a blurring update image.

[0014] In a third aspect, an embodiment of the present application further provides a device, comprising: a processor and a memory, wherein the memory stores instructions, and the instructions are loaded and executed by the processor to implement the method described above.

[0015] In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0016] The advantages or beneficial effects of the above technical solution include at least: a picture blur processing method of the present application can achieve a better highlighting effect; and while achieving the blur effect, the calculation speed can be improved by partition blur.

[0017] The above summary is for illustrative purposes only and is not intended to be limiting in any way. In addition to the illustrative aspects, embodiments and features described above, further aspects, embodiments and features of the present application will be readily apparent by reference to the accompanying drawings and the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In the accompanying drawings, unless otherwise specified, the same reference numerals throughout the multiple drawings represent the same or similar parts or elements. These drawings are not necessarily drawn to scale. It should be understood that these drawings only depict some embodiments disclosed in the present application and should not be regarded as limiting the scope of the present application.

[0019] Figure 1 This is a flowchart of the image blur processing method according to an embodiment of the present application.

[0020] Figure 2 This is a schematic diagram of an in-vehicle display interface image of an embodiment of the present application.

[0021] Figure 3 This is a flowchart of performing fuzzy update processing on areas where data information has changed according to an embodiment of the present application.

[0022] Figure 4 This is a flowchart of performing fuzzy update processing on areas where data information has changed according to an embodiment of the present application.

[0023] Figure 5 This is an enlarged schematic diagram of the area where data information has changed in an embodiment of the present application.

[0024] Figure 6This is a flowchart of performing fuzzy update processing on areas where data information has changed according to an embodiment of the present application.

[0025] Figure 7 A compressed schematic diagram of the target area of ​​an embodiment of the present application.

[0026] Figure 8 This is a flowchart of performing fuzzy update processing on areas where data information has changed according to an embodiment of the present application.

[0027] Fig. 9 This is a flowchart of the fuzzy processing according to an embodiment of the present application.

[0028] Fig.10 Flow chart of a method for blurring a driving image according to an embodiment of the present application.

[0029] Fig.11 Schematic diagram of the structure of the image blur processing device according to an embodiment of the present application.

[0030] Fig.12 This is an application flow chart of the image blur processing device according to an embodiment of the present application.

[0031] Fig.13 This is a structural block diagram of the device according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present application. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0033] The image blurring method of the present application is suitable for an in-vehicle human-computer interaction interface, and can update the blurred background to achieve a better highlighting effect. Meanwhile, the blurred background is not updated for all images to be blurred, but the blurred images are partitioned according to changes in data information, and only the areas where data information has changed are blurred and updated. The partition blurring can be used to improve the calculation speed while achieving the blurring effect.

[0034] Figure 1 This is a flow chart of the image blur processing method according to an embodiment of the present application. Figure 1 The specific steps of a picture blur processing method of the present application are as follows:

[0035] Step S1: determine a picture to be blurred, wherein the picture to be blurred includes data information.

[0036] First, determine the interface to be processed. This application is to highlight a part of the interface to be processed. Therefore, before blurring, the interface to be processed needs to be divided into a highlight window that is not blurred and a background image that is blurred. The interface to be processed includes a background image and a highlight window covering the background image; the background image is an image that has not been blurred, or is a blurred image, or is a blurred update image; the background image is used as the image to be blurred. Among them, the determined image to be blurred contains data information. The highlight window is a pop-up window, a dialog box, etc., but it is not limited to this, as long as it is a picture that the user needs to highlight.

[0037] After determining the image to be blurred, you need to partition the image to be blurred. Specifically:

[0038] Step S2: dividing the image to be blurred into at least two areas according to changes in the data information in the image to be blurred, wherein the areas obtained after the division contain data information.

[0039] Specifically, monitoring the change characteristics of the data information in the image to be blurred, partitioning the image to be blurred based on the change characteristics to obtain at least two regions. The change characteristics are the change frequency, number of changes, or size of the change region of the data information.

[0040] Specifically, the steps for dividing the area are:

[0041] (1) Divided into two areas:

[0042] The image to be blurred can be divided into two areas, one area where the data information does not change, and the other area where the data information changes. The area where the data information changes does not consider the unevenness of the data change. As long as the data changes, it is divided into the area where the data information changes.

[0043] (2) When divided into more than two areas:

[0044] The image to be blurred can also be divided into more than two areas, including at least one area where the data information does not change, and at least two areas where the data information changes. If there are parts with different change frequencies in the data information, it can be subdivided into several areas with smaller data information changes. However, the change feature is not limited to the change frequency. As long as the feature in the data information changes, the change feature can be used to divide the area.

[0045] The following is a specific example to illustrate how to divide the regions. Figure 2 This is a schematic diagram of an in-vehicle display interface image of an embodiment of the present application.

[0046] See also Figure 2 , the figure includes parts A, B, C and D. Part A is the static background area, B is the speed display area, C is the pop-up window display area, and D is the warning display area. Among them, part C is the highlighted display window; at a certain moment, only the speed changes, and part B is the area where the data information changes. The width and height of part B can change, and part B is fuzzy updated; while the width and height of parts A and D do not change, and the data information does not change. Part A and D are both areas where the data information does not change.

[0047] Through such partitioning processing, only the areas where the data information has changed are fuzzy updated, while the areas where the data information has not changed use the original cached image data and do not need to be re-fuzzy updated and drawn, which greatly reduces the time spent on fuzzy update processing, thereby improving the calculation speed and saving system memory.

[0048] Step S3, detecting that there is an area where the data information has changed, and performing fuzzy update processing on the area where the data information has changed;

[0049] After the division of regions is completed, the regions where data information has changed need to be fuzzy updated. Figure 3 This is a flowchart of performing fuzzy update processing on a region where data information has changed according to an embodiment of the present application. The following is a detailed description of a specific processing method for performing fuzzy update processing on a region where the data information has changed:

[0050] Step S31: using a preset blur radius to perform blur processing on the area where the data information has changed.

[0051] In this application, a Gaussian blur algorithm with a general parameter blur radius is used for blurring, and the same blur radius is used to perform blurring of partitioned areas of different sizes to a consistent degree. The Gaussian blur algorithm is a prior art and is not described in detail here. The larger the blur radius, the more time-consuming the calculation. The blur requirement can be met by combining the third partition area after the above compression processing. The blur radius can be adjusted according to actual needs. Preferably, the blur radius is set to 2.

[0052] The above-mentioned fuzzification process can achieve a fuzzification effect, but the fuzzification effect is not ideal. After the fuzzification process is performed on the areas where different data information has changed, the actual splicing process may cause marginalization and background inconsistency. In this application, the interception range is expanded when there is an area where the data information has changed, and the excess part is intercepted after the fuzzification process, so as to achieve overall unity.

[0053] Figure 4 This is a flow chart of performing fuzzy update processing on a region where data information has changed according to an embodiment of the present application. Specifically, before the fuzzy processing is performed, it also includes:

[0054] Step S32, extracting a target area from the image to be blurred, wherein the target area includes the area where the data information has changed and at least a portion of a surrounding area corresponding to the area where the data information has changed;

[0055] The intercepted target area is fuzzified, and the target area is scaled after the fuzzification process, so that the scaled area matches the area characteristics of the area where the data information is changed and is included in the target area. That is, the scaled area is the same size as the area where the data information is changed.

[0056] Preferably, all sides of the area where the data information has changed are enlarged at the same proportion, and the enlarged area is the target area; it is also possible to enlarge only certain sides of the area where the data information has changed. For example, when the left side of the area where the data information has changed coincides with the left side of the overall image to be blurred, only the upper and lower sides and the right side of the area where the data information has changed are enlarged, and a preset enlargement ratio a is set in advance. The preset enlargement ratio a of each side of the area where the data information has changed may be the same or different.

[0057] Figure 5 This is an enlarged schematic diagram of the area where the data information of the embodiment of the present application is changed. Please refer to Figure 5 In the figure, E1 is the area where the data information changes, and E2 is the target area after expansion. Figure 3 The enlargement ratio is set to 5 / 4, that is, the ratio of E2's height to E1's height is 5 / 4, and the ratio of E2's width to E1's width is 5 / 4.

[0058] When fuzzifying areas where data information has changed, if different areas are fuzzified using the same fuzzy parameters, it will save system operating costs; however, using the same fuzzy parameters may result in inconsistent fuzziness in areas where data information of different sizes has changed. In order to ensure that the same fuzzy parameters, i.e., the same fuzzy radius r, can be used for areas where different data information has changed, and to show consistency in fuzziness, the areas where different data information has changed will be compressed according to their sizes.

[0059] Figure 6 This is a flow chart of performing fuzzy update processing on a region where data information has changed according to an embodiment of the present application. Specifically, before the fuzzy processing is performed, it also includes:

[0060] Step S33: compress at least the area where the data information has changed, so as to perform fuzzy processing on the compressed area where the data information has changed.

[0061] The following is a detailed description of the compression ratio acquisition process:

[0062] Specifically, the compression ratio of the image to be blurred is obtained; and the compression ratio corresponding to the area to be compressed is obtained, so as to perform compression processing based on the area where the data information has changed.

[0063] The following is an example of a method for setting the compression ratio of each area where the data information has changed:

[0064] The height of the overall image to be blurred is H1, the width of the overall image to be blurred is L1, the height of the target area is H2, the width of the target area is L2, and the scaling ratio of the overall image to be blurred is selected as SIZE. Preferably, the scaling ratio of the overall image to be blurred is SIZE∈(2,10).

[0065] Then, set the high compression ratio size(h) of the target area and the wide compression ratio size(l) of the target area; then the high compression ratio size(h) of the target area = max(((H2 / H1)×SIZE, SIZE0), the wide compression ratio size(l) of each target area = max(((L2 / L1)×SIZE, SIZE0), among which SIZE0 = 2 times is selected for comparison, that is, it must be scaled at least 2 times.

[0066] Figure 7 This is a compressed schematic diagram of the target area of ​​the embodiment of the present application. Figure 7 , the compression ratio of the whole image to be blurred is selected as SIZE=4, H1=5cm, L1=7cm, H2=4cm, L2=3cm, SIZE0=2. Then the high compression ratio size(h)=max(((4 / 5)×4,2)=3.2 of the target area is calculated, and the wide compression ratio size(l)=max(((3 / 7)×4,2)=2 of the target area is calculated. It can be seen that the target area and the image to be blurred are compressed according to different compression ratios, and the high compression ratio and wide compression ratio of the target area can also be different.

[0067] The above-mentioned method for setting the compression ratio is a method for calculating the compression ratio of the target area after expanding the area where the data information has changed. It is also possible to directly calculate the compression ratio of the area where the data information has changed without expanding the area where the data information has changed.

[0068] Before the fuzzy processing is performed, step S32 or step S33 may be included, respectively. Figure 4 , Figure 6 As shown; Figure 8 This is a flow chart of performing fuzzy update processing on a region where data information has changed according to an embodiment of the present application, wherein steps S32 and S33 are performed in sequence before entering the fuzzy processing process.

[0069] Step S4, merging the area after the blur update processing with the remaining area of ​​the to-be-blurred image that has not been blurred and updated, to obtain a blur update image. Finally, covering the highlight display window on the blur update image for highlight display.

[0070] Based on the above steps, Fig. 9 For a flowchart of the fuzzy processing of the embodiment of the present application, please refer to Fig. 9 ,Specifically, the process steps of fuzzy processing are:

[0071] a. Start;

[0072] b. When no data information change is detected, determine whether there is display cache. If there is display cache data, submit the display cache data and enter step i. If there is no display cache, enter step d to start fuzzy processing.

[0073] c. When a change in data information is detected, the process goes to step d and begins fuzzification processing;

[0074] d. Get the native image and the display cache data of the area where the current data information has changed;

[0075] e. Plan the blurred area based on the original image obtained;

[0076] f. Preprocess the blurred area to obtain a compressed native image;

[0077] g. Use Gaussian blur algorithm to blur the compressed native image, and use ScriptIntrinsicBlur of Android's renderscript library to implement it:

[0078] ScriptIntrinsicBlur.create(renderScript,Element.U8_4(renderScript));

[0079] scriptIntrinsicBlur.setRadius(radius);

[0080] scriptIntrinsicBlur.setInput(allIn);

[0081] scriptIntrinsicBlur.forEach(allOut);

[0082] allOut.copyTo(outBitmap)

[0083] h. Submit the image obtained after blurring and proceed to step i;

[0084] i. Integrate the submitted images into a complete frame and submit it to the system for drawing.

[0085] Based on the entire method of dynamic blur background, this application provides a specific embodiment for illustration. Fig.10 This is a flow chart of a method for blurring a driving image in an embodiment of the present application, specifically:

[0086] a. Determine the interface to be processed;

[0087] b. Divide the interface to be processed into several rectangular areas according to the changes in data information and monitor the changes in the corresponding data information;

[0088] c. Draw the pop-up screen part once and cache it;

[0089] d. The image to be blurred is divided into different areas according to the change of data information, and the areas are intercepted respectively;

[0090] e. Use the Gaussian fuzzy algorithm with general parameters for fuzzy processing;

[0091] f. Merge the area images where the data information has changed after the fuzzy processing into a complete interface image;

[0092] h. Submit the complete interface image to the system for drawing;

[0093] i. Monitor the data information of the image to be blurred in real time, re-match the partitions according to the data information, and return to step e according to the area where the data information has changed.

[0094] The present invention also conducts an experimental comparison on the performance of two schemes, namely, global dynamic update fuzzy processing A and partition dynamic update fuzzy processing B, and illustrates the performance effect through the experimental results:

[0095] In the experiment: global dynamic update fuzzy processing and partition dynamic update fuzzy processing both use the same layout, two update areas, the update cycles of the two update areas are 100ms and 500ms respectively, and the cumulative update is 500 times. The performance of the two solutions is tested from three indicators: CPU usage, memory usage and running time:

[0096] plan CPU(%) Memory (MB) Cumulative calculation time (ms) A 40 85 50000 B 40 60 5000

[0097] Table 1

[0098] As can be seen from Table 1, the performance of the partitioned dynamic update fuzzy processing scheme B is better than that of the global dynamic update fuzzy processing scheme A. This is because the global dynamic update fuzzy processing scheme essentially needs to traverse the cache of all current images, while the partitioned dynamic update fuzzy processing scheme B does not need to traverse the cache of all current images. As the update area increases, the performance advantage of the partitioned dynamic update fuzzy processing scheme becomes more obvious.

[0099] Based on the above-mentioned method for dynamically blurring the background, the present application also provides a device for image blurring processing. Fig.11 This is a schematic diagram of the structure of the image blur processing device according to the embodiment of the present application. Fig.11 The image blur processing device 1 comprises:

[0100] A first picture determination module 100 is used to determine a picture to be blurred, wherein the picture to be blurred includes data information;

[0101] A partitioning module 200, configured to divide the image to be blurred into at least two regions according to changes in the data information in the image to be blurred, wherein the regions obtained after the division contain data information;

[0102] The image processing module 300 is used to detect the area where the data information has changed, and perform fuzzy update processing on the area where the data information has changed;

[0103] The image merging module 400 is used to merge the area after the blurring update processing with the remaining area of ​​the image to be blurred that has not been blurred and updated, so as to obtain a blurring update image.

[0104] The image blur processing device 1 further includes:

[0105] The second image determination module 500 is used to determine the interface to be processed, wherein the interface to be processed includes a background image and a highlighted display window covering the background image; the background image is an image that has not been blurred, or is an image that has been blurred, or is an image that has been blurred and updated; the background image is used as the image to be blurred.

[0106] The image blur processing device 1 further includes:

[0107] The display module 600 is used to cover the highlight window on the fuzzy processing update graph to perform highlight display.

[0108] The partition module 200 includes:

[0109] A data monitoring unit 210, configured to monitor the change characteristics of the data information in the image to be blurred;

[0110] The determination partition unit 220 is used to partition the image to be blurred based on the change characteristics to obtain at least two areas.

[0111] The image processing module 300 includes:

[0112] The fuzzy processing unit 310 is used to perform fuzzy processing on the area where the data information has changed using a preset fuzzy radius.

[0113] The image processing module 300 further includes:

[0114] The region interception unit 320 is used to intercept a target region from the image to be blurred, wherein the target region includes the region where the data information has changed and at least a portion of a surrounding region corresponding to the region where the data information has changed;

[0115] The area blurring unit 330 is used to blur the captured target area and scale the target area after blurring so that the scaled area matches the area features of the target area where the data information has changed.

[0116] The image processing module 300 further includes:

[0117] The region compression unit 340 is used to compress at least the region where the data information has changed, so as to perform fuzzy processing on the region where the data information has changed after the compression processing.

[0118] The image processing module 300 further includes:

[0119] A compression ratio acquisition unit 350, used to acquire the compression ratio of the image to be blurred;

[0120] The compression ratio calculation unit 360 is used to obtain the compression ratio corresponding to the area to be compressed, so as to facilitate compression processing based on the area where the data information has changed.

[0121] It also includes: a cache module 700, which is used to cache the image information of the image to be blurred, including the image information of the area where the data information has changed, and the image information of the area where the data information has not changed.

[0122] The functions of each module in each device in the embodiments of the present application can be found in the corresponding description in the above method, and will not be repeated here.

[0123] Based on the above-mentioned image blur processing device, Fig.12 This is an application flow chart of the image blur processing device according to an embodiment of the present application. The specific process steps are as follows: Fig.12 As shown,

[0124] a. Start, pre-partition;

[0125] b. The data monitoring unit monitors the changing characteristics of the data information in the image to be blurred;

[0126] c. The judgment partitioning unit further partitions the pre-partitioned area of ​​the blurred image based on the change characteristics to obtain at least two areas;

[0127] d. The image processing module detects an area where data information has changed, performs fuzzy update processing on the area where data information has changed, and caches the image information of the area where data information has changed in the cache module;

[0128] e. The image merging module merges the area after the fuzzy update processing with the remaining area of ​​the image to be fuzzy processed that has not been fuzzy updated, and obtains the fuzzy processing update image. Among them, the image information of the area where the data information has not changed is obtained from the cache module;

[0129] f. Submit the blurred updated image for drawing.

[0130] The present application also provides a device, including: a memory 910 and a processor 920, wherein the memory 910 stores instructions, and the instructions are loaded and executed by the processor 920 to implement the above method.

[0131] Fig.13 FIG. 2 shows a structural block diagram of a device according to an embodiment of the present application. Fig.13 As shown, the device includes: a memory 910 and a processor 920, wherein the memory 910 stores a computer program that can be run on the processor 920. When the processor 920 executes the computer program, the image blur processing method in the above embodiment is implemented. The number of the memory 910 and the processor 920 can be one or more.

[0132] The device also includes:

[0133] The communication interface 930 is used to communicate with external devices and perform data exchange transmission.

[0134] If the memory 910, the processor 920 and the communication interface 930 are implemented independently, the memory 910, the processor 920 and the communication interface 930 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Fig.13 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0135] Optionally, in a specific implementation, if the memory 910, the processor 920 and the communication interface 930 are integrated on a chip, the memory 910, the processor 920 and the communication interface 930 can communicate with each other through an internal interface.

[0136] An embodiment of the present invention provides a computer-readable storage medium storing a computer program, which implements the method provided in the embodiment of the present application when the program is executed by a processor.

[0137] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. It is worth noting that the processor may be a processor supporting the advanced RISC machines (ARM) architecture.

[0138] Further, optionally, the above-mentioned memory may include a read-only memory and a random access memory, and may also include a non-volatile random access memory. The memory may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may include a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may include a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available. For example, static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM) and direct rambus RAM (DR RAM).

[0139] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.

[0140] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples, unless they are contradictory.

[0141] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0142] Any process or method description in the flow chart or otherwise described herein can be understood to represent a module, fragment or portion of a code including one or more executable instructions for implementing the steps of a specific logical function or process. And the scope of the preferred embodiment of the present application includes other implementations, in which the functions may not be performed in the order shown or discussed, including in a substantially simultaneous manner or in a reverse order according to the functions involved.

[0143] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, which can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processor or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0144] It should be understood that the various parts of the present application can be implemented with hardware, software, firmware or a combination thereof. In the above embodiments, multiple steps or methods can be implemented with software or firmware stored in a memory and executed by a suitable instruction execution system. All or part of the steps of the above embodiment method can be completed by instructing the relevant hardware through a program, which can be stored in a computer-readable storage medium, and when the program is executed, it includes one of the steps of the method embodiment or a combination thereof.

[0145] In addition, each functional unit in each embodiment of the present application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into one module. The above-mentioned integrated module can be implemented in the form of hardware or in the form of a software functional module. If the above-mentioned integrated module is implemented in the form of a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. The storage medium can be a read-only memory, a disk or an optical disk, etc.

[0146] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of various changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for image blurring, characterized in that: include: Determine an interface to be processed, wherein the interface to be processed includes a background image and a highlighted display window covering the background image; the background image is an image that has not been blurred, or is an image that has been blurred, or is an image that has been blurred and updated, and the background image is used as the image to be blurred, wherein the image to be blurred includes data information; Dividing the image to be blurred into at least two regions according to the change of the data information in the image to be blurred, wherein the regions obtained after the division contain data information; Detecting that there is an area where the data information has changed, and performing fuzzy update processing on the area where the data information has changed; The area after the blur update processing is merged with the remaining area of ​​the image to be blurred that has not been blurred and updated to obtain a blur update image.

2. The image blur processing method according to claim 1, characterized in that: Also includes: The highlight window is overlaid on the blur processing update map to perform highlighting.

3. The image blur processing method according to claim 1, characterized in that: The step of dividing the image to be blurred into at least two areas according to the change of the data information in the image to be blurred includes: Monitoring the change characteristics of the data information in the image to be blurred; The image to be blurred is partitioned based on the change characteristics to obtain at least two regions.

4. The image blur processing method according to claim 1 or 3, characterized in that: The fuzzy updating process of the area where the data information has been changed includes: A preset blur radius is used to perform blur processing on the area where the data information has changed.

5. The image blur processing method according to claim 4, characterized in that: Before the fuzzy processing is performed, the method further includes: Cutting out a target area from the image to be blurred, the target area including the area where the data information has changed and at least a portion of a surrounding area corresponding to the area where the data information has changed; The intercepted target area is subjected to fuzzification processing, and after the fuzzification processing, the target area is scaled so that the scaled area matches the regional features of the area in the target area where the data information is changed.

6. The image blur processing method according to claim 4, characterized in that: Before the fuzzy processing is performed, the method further includes: At least the region where the data information has been changed is compressed, so as to facilitate fuzzy processing on the compressed region where the data information has been changed.

7. The image blur processing method according to claim 6, characterized in that: Also includes: Obtaining the compression ratio of the image to be blurred; A compression ratio corresponding to the area to be compressed is obtained, so as to perform compression processing based on the area where the data information has changed.

8. A device for image blur processing, characterized in that: include: The second image determination module is used to determine the interface to be processed, wherein the interface to be processed includes a background image and a highlighted display window covering the background image; the background image is an image that has not been blurred, or is an image that has been blurred, or is an image that has been blurred and updated; the background image is used as the image to be blurred; A first picture determination module is used to determine a picture to be blurred, wherein the picture to be blurred includes data information; a partitioning module is used to divide the picture to be blurred into at least two areas according to a change of the data information in the picture to be blurred, wherein the area obtained after the division includes data information; An image processing module is used to detect the area where the data information has changed, and perform fuzzy update processing on the area where the data information has changed; The image merging module is used to merge the area after the blurring update processing with the remaining area of ​​the image to be blurred that has not been blurred and updated, so as to obtain a blurring update image.

9. The image blur processing device according to claim 8, characterized in that: Also includes: The display module is used to cover the highlight window on the fuzzy processing update graph to perform highlight display.

10. The image blur processing device according to claim 8, characterized in that: The partition module comprises: A data monitoring unit, used to monitor the change characteristics of the data information in the image to be blurred; The determination partitioning unit is used to partition the image to be blurred based on the change characteristics to obtain at least two areas.

11. The image blur processing method according to claim 8 or 10, characterized in that: The image processing module includes: The fuzzy processing unit is used to use a preset fuzzy radius to perform fuzzy processing on the area where the data information has changed.

12. The image blur processing device according to claim 11, characterized in that: The image processing module further includes: A region interception unit, configured to intercept a target region from the image to be blurred, wherein the target region includes the region where the data information has changed and at least a portion of a surrounding region corresponding to the region where the data information has changed; The area blurring unit is used to blur the captured target area and scale the target area after blurring so that the scaled area matches the area features of the target area where the data information has changed.

13. The image blur processing device according to claim 11, characterized in that: The image processing module further includes: The region compression unit is used to compress at least the region where the data information has changed, so as to facilitate fuzzy processing of the region where the data information has changed after the compression processing.

14. The image blur processing device according to claim 13, characterized in that: The image processing module further includes: A compression ratio acquisition unit, used to acquire the compression ratio of the image to be blurred; The compression ratio calculation unit is used to obtain the compression ratio corresponding to the area to be compressed, so as to facilitate compression processing based on the area where the data information has changed.

15. A device, characterized in that include: A processor and a memory, wherein the memory stores instructions, and the instructions are loaded and executed by the processor to implement the method according to any one of claims 1 to 7. 16 . A computer-readable storage medium, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, the method according to claim 1 is implemented.

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