An image display method, device and terminal equipment

Abstract

Embodiments of the present application relate to the technical field of image processing, and provide an image display method and device, a terminal device, a computer readable storage medium, and a computer program product. An image obtained by downsampling an initial image (a first frame in an image sequence) is displayed on a display screen of a terminal device, and the initial image is processed to add noise. Since the preview image and the processed image are both generated based on the same reference frame, the preview image can be quickly obtained, and the image before and after switching can be consistent when the preview image is switched to the processed image, thereby avoiding or improving the jumping of the image displayed on the display screen of the terminal device, and improving the visual experience of the user and the experience of using the terminal device to take a picture.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of image processing, and in particular to an image display method, an image display device and a terminal device. BACKGROUND

[0002] At present, in order to meet the needs of users to obtain good-quality images when taking images in multiple scenes through a terminal device, the terminal device usually processes a plurality of image sequences including an initial image (i.e., a first frame of image) based on the initial image through an image processing algorithm after the initial image is captured, so as to improve the image quality, and then provides the processed result image to the user, so as to improve the user's shooting experience.

[0003] However, with the improvement of image quality, the image processing algorithm used on the terminal device is becoming more and more complex, and the running time of the complex algorithm is becoming longer and longer, which leads to a longer image processing time, and finally results in the situation that the processed result image cannot be quickly displayed for the user, so that the user cannot timely preview the captured image to check the shooting effect of the terminal device, and the user has a poor shooting experience.

[0004] In order to enable the user to quickly preview the captured image, the terminal device generates a preview image based on the camera preview stream data when the image is captured, displays the preview image to the user first, and then replaces the preview image with the processed result image after the processed result image is generated. The so-called preview image refers to a picture in the interface that can be previewed by the user, and the so-called processed result image refers to a picture displayed in a large picture floating layer after the user clicks on a thumbnail, which is obtained through an algorithm based on the camera shooting stream data when the image is captured.

[0005] However, due to the shutter lag and / or different preview image acquisition strategies of the terminal device in the process of capturing the image, when a moving scene is captured, the preview image and the processed result image may not be consistent in the picture, so that when the terminal device displays the preview image and replaces it with the processed result image, the display picture will jump, resulting in the situation that the preview image and the processed result image displayed to the user are inconsistent, which causes a poor visual experience for the user. SUMMARY

[0006] The embodiments of the present application provide an image display method, which can avoid or improve the problem that the preview image and the processed result image displayed on the terminal device are inconsistent.

[0007] The first aspect of the embodiments of the present application provides an image display method, which comprises:

[0008] obtaining an initial image, the initial image being a reference frame for generating a processed result image;

[0009] Downsample the initial image according to a predetermined sampling rate to obtain a target image;

[0010] Process the noise in the target image to obtain a preview image;

[0011] Display the preview image at a preview display position;

[0012] Process an image sequence containing the initial image through an image processing algorithm to obtain a processing result image;

[0013] Replace the preview image displayed at the preview display position with the processing result image.

[0014] In an optional method embodiment, the above method further comprises:

[0015] Remove isolated pixel points in the target image through a median filtering method to obtain a first image;

[0016] Perform noise reduction processing on the first image based on a wavelet noise reduction method to obtain a preview image.

[0017] In an optional method embodiment, the above method further comprises:

[0018] Obtain the gray scale values of all initial pixel points within a two-dimensional template range from the target image;

[0019] Sort the gray scale values of all initial pixel points according to an arrangement order, and take the gray scale value of an initial pixel point arranged in the middle as a gray scale median value;

[0020] Process each isolated pixel point in the target image based on the gray scale median value to obtain each target pixel point, wherein the isolated pixel point refers to an initial pixel point at the center position of the two-dimensional template;

[0021] Obtain a first image based on each target pixel point and each initial pixel point.

[0022] In an optional method embodiment, the above method further comprises:

[0023] Assign the gray scale value of each isolated pixel point to the gray scale median value to obtain each target pixel point.

[0024] In an optional method embodiment, the above method further comprises:

[0025] Process noise points in the first image through a wavelet noise reduction method to obtain a second image;

[0026] Obtain a preview image based on the result of smoothing processing on the second image.

[0027] In an optional method embodiment, the method further comprises:

[0028] wavelet-decomposing the first image to obtain each detail component and each approximation component, the detail component being a high-frequency part in the first image, and the approximation component being a low-frequency part in the first image;

[0029] threshold-quantizing each detail component based on a predetermined threshold to obtain each quantized component;

[0030] wavelet-reconstructing each quantized component and each approximation component to obtain the second image.

[0031] In an optional method embodiment, the method further comprises:

[0032] obtaining light sensitivity data when the terminal device collects the initial image;

[0033] determining image blurriness corresponding to the light sensitivity data based on the light sensitivity data and the corresponding relationship information; the corresponding relationship information includes a plurality of light sensitivity data and image blurriness corresponding to the plurality of light sensitivity data;

[0034] performing smoothing processing on the second image based on the image blurriness through a Gaussian blur algorithm to obtain the preview image.

[0035] A second aspect of an embodiment of the present application provides an image display device, the device comprising:

[0036] an obtaining module configured to obtain an initial image, the initial image being a reference frame for generating a processing result image;

[0037] a sampling module configured to down-sample the initial image according to a predetermined sampling rate to obtain a target image;

[0038] a processing module configured to process noise in the target image to obtain a preview image;

[0039] a display module configured to display the preview image at a preview display position;

[0040] the processing module is further configured to process an image sequence containing the initial image through an image processing algorithm to obtain a processing result image;

[0041] the display module is further configured to replace the preview image displayed at the preview display position with the processing result image.

[0042] A third aspect of an embodiment of the present application provides an image display device, comprising:

[0043] a processor and a memory for storing processor-executable instructions;

[0044] The processor is configured to read executable instructions from the memory and execute the instructions to implement the image display method according to the first aspect.

[0045] The fourth aspect of the embodiment of the present application provides a terminal device, comprising:

[0046] The processor and the memory for storing processor-executable instructions;

[0047] The processor is configured to read executable instructions from the memory and execute the instructions to implement the image display method according to the first aspect.

[0048] The fourth aspect of the embodiment of the present application provides a terminal device, comprising:

[0049] The processor and the memory for storing processor-executable instructions;

[0050] The processor is configured to read executable instructions from the memory and execute the instructions to implement the image display method according to the first aspect.

[0051] The fourth aspect of the embodiment of the present application provides a terminal device, comprising:

[0052] The processor and the memory for storing processor-executable instructions;

[0053] The processor is configured to read executable instructions from the memory and execute the instructions to implement the steps of the image display method according to the first aspect.

[0054] The fifth aspect of the embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the image display method according to the first aspect.

[0055] The sixth aspect of the embodiment of the present application provides a computer program product, comprising a computer program, and the computer program is executed by a processor to implement the steps of the image display method according to the first aspect.

[0056] The technical scheme provided by the embodiment of the present application can at least achieve the following beneficial effects:

[0057] The image display method, device, terminal device, computer readable storage medium and computer program product provided by the embodiments of the present application, when a user takes an image through a terminal device, the image sequence used to generate a processing result image (the processing result image is also the final photographing effect image displayed on the display screen of the terminal device) is obtained after clicking the shooting key set in the terminal device. The terminal device can obtain the processing result image after corresponding processing of the image sequence through an image processing algorithm. Then, in the case that the terminal device has not completed the processing of the image sequence to obtain the final processing result image, in order to let the user preview the image taken in time to judge whether the expected photographing effect is met, the embodiments of the present application can display a preview image on the display screen of the terminal device by performing down-sampling on the initial image (the first frame in the image sequence) and performing noise processing on the initial image. Since the reference frame of the preview image and the final processing result image is consistent, the preview image can be quickly obtained, and the image consistent before and after switching can be presented to the user when the preview image is switched to the final processing result image, so that the jumping of the picture displayed on the display screen of the terminal device is avoided or improved, and the visual experience of the user and the experience of taking a photograph through the terminal device are improved. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 FIG. 1 is a hardware structure diagram of a terminal device according to an example embodiment of the present application;

[0059] Figure 2 FIG. 2 is a software structure diagram of a terminal device according to an example embodiment of the present application;

[0060] Figure 3 FIG. 3 is an application scenario diagram of an image display method according to an example embodiment of the present application;

[0061] Figure 4a FIG. 4 is a preview image displayed on a terminal device according to an example embodiment of the present application;

[0062] Figure 4b FIG. 5 is a processing result image displayed on a terminal device according to an example embodiment of the present application;

[0063] Figure 5 FIG. 6 is an interface diagram of a display screen loading an image of a terminal device according to an example embodiment of the present application;

[0064] Figure 6 FIG. 7 is a flowchart of an image display method according to an example embodiment of the present application;

[0065] Figure 7 FIG. 8 is a schematic diagram of an image sequence collected by a terminal device according to an example embodiment of the present application;

[0066] Figure 8a Fig. 1 is a schematic diagram of a display screen of a terminal device displaying a preview image according to an example embodiment of the present application;

[0067] Figure 8b Fig. 2 is a schematic diagram of a display screen of a terminal device displaying a processing result image according to an example embodiment of the present application;

[0068] Figure 9 Fig. 3 is a flowchart of another image display method according to an example embodiment of the present application;

[0069] Figure 10 Fig. 4 is a flowchart of another image display method according to an example embodiment of the present application;

[0070] Figure 11a Fig. 5 is an image before median filter processing according to an example embodiment of the present application;

[0071] Figure 11b Fig. 6 is an image after median filter processing according to an example embodiment of the present application;

[0072] Figure 12 Fig. 7 is a flowchart of another image display method according to an example embodiment of the present application;

[0073] Figure 13 Fig. 8 is a flowchart of another image display method according to an example embodiment of the present application;

[0074] Figure 14 Fig. 9 is a flowchart of another image display method according to an example embodiment of the present application;

[0075] Figure 15a Fig. 10 is an interface change diagram of a display screen of a terminal device switching from displaying a thumbnail to displaying a preview image according to an example embodiment of the present application;

[0076] Figure 15b Fig. 11 is an interface change diagram of a display screen of a terminal device switching from displaying a preview image to displaying a processing result image according to an example embodiment of the present application;

[0077] Figure 16 Fig. 12 is a complete flowchart of an image display method according to an example embodiment of the present application;

[0078] Figure 17 Fig. 13 is a structural block diagram of an image display device according to an example embodiment of the present application;

[0079] Figure 18 Fig. 14 is an internal structure diagram of a terminal device according to an example embodiment of the present application. DETAILED DESCRIPTION

[0080] The exemplary embodiments will be described in detail herein with reference to the attached drawings. The following description is made with reference to the accompanying drawings in which like reference numerals refer to like elements, unless the context clearly shows otherwise. The following description of exemplary embodiments is not representative of all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with some aspects of the present application as detailed in the appended claims.

[0081] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term "and / or," as used herein, refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0082] It will be understood that, although the terms first, second, third, etc. can be used herein to describe various information, these terms are not intended to denote a temporal or chronological order. Rather, these terms are used solely to distinguish one from another. For example, a first information can be termed a second information, and, similarly, a second information can be termed a first information, without departing from the scope of the present application. The word "if" can be interpreted as meaning "when" or "upon" or "in response to determining," depending on the context.

[0083] The image display method of the embodiments of the present application can be applied to a terminal device, which can be, for example, a smartphone, a phone watch, a notebook computer, a tablet computer, or the like held by a user. The embodiments of the present application do not limit the specific type of the terminal device.

[0084] As Figure 1As shown, the terminal device 100 can include an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a loudspeaker 170A, a receiver 170B, a microphone 170C, an earphone interface 170D, a sensor module 180, a key 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 can include a pressure sensor 180A, a gyroscope sensor 180B, a barometric pressure sensor 180C, a magnetic sensor 180D, an acceleration sensor 180E, a distance sensor 180F, a proximity light sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0085] It can be understood that the structure shown in the embodiments of the present application does not constitute a specific limitation on the terminal device 100. In other embodiments of the present application, the terminal device 100 can include more or fewer components than shown, or combine certain components, or split certain components, or different component arrangements. The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0086] The processor 110 can include one or more processing units, for example: the processor 110 can include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Different processing units can be independent devices, or can be integrated in one or more processors.

[0087] The processor can further include a memory for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. The memory can hold instructions or data that the processor has just used or is using repeatedly, and can be directly called from the memory. This avoids repeated access and reduces the waiting time of the processor, thereby improving the processing efficiency of the image.

[0088] The internal memory 121 can be used to store computer executable program codes, and the executable program codes include instructions. The processor 110 performs various functional applications and data processing of the electronic device 100 by running the instructions stored in the internal memory 121. The internal memory 121 can include a program storage area and a data storage area. The program storage area can store an operating system, at least one application program required by a function (such as a sound playing function, an image playing function, etc.), and the like. The data storage area can store data (such as audio data, a phone book, etc.) created during the use of the electronic device 100, and the like. In addition, the internal memory 121 can include a high-speed random access memory, and can further include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, a universal flash memory (UFS), and the like.

[0089] The terminal device 100 realizes the display function through the GPU, the display screen 194, and the application processor, etc. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations for image processing. The processor 110 can include one or more GPUs, which execute program instructions to generate or change display images.

[0090] The display screen 194 is used to display images, videos, etc. The display screen 194 includes a display panel. The display panel can adopt a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a Miniled, a MicroLed, a Micro-oLed, a quantum dot light-emitting diode (QLED), etc. In some embodiments, the terminal device 100 can include 1 or N display screens 194, and N is a positive integer greater than 1.

[0091] Touch sensor 180K, also referred to as "touch panel". Touch sensor 180K can be disposed on display screen 194, and touch sensor 180K and display screen 194 together form a touch screen, also referred to as "touch panel". Touch sensor 180K is configured to detect a touch operation applied to or near the touch sensor 180K. The touch sensor can pass the detected touch operation to the application processor to determine the touch event type. Visual output related to the touch operation can be provided through display screen 194. In other embodiments, touch sensor 180K can also be disposed on the surface of terminal device 100, which is different from the position where display screen 194 is located.

[0092] The software system of terminal device 100 can adopt a layered architecture, an event-driven architecture, a microkernel architecture, a microservice architecture, or a cloud architecture. The software structure of terminal device 100 according to an embodiment of the present application is exemplarily described by taking an Android system with a layered architecture as an example.

[0093] Figure 2 is a software structure block diagram of terminal device 100 according to an embodiment of the present application. The layered architecture divides the software into several layers, and each layer has a clear role and division of labor. The layers communicate with each other through software interfaces. In some embodiments, the Android system is divided into four layers, from top to bottom, which are the application layer, the application framework layer, the Android runtime and system library, and the kernel layer.

[0094] The application layer can include a series of application packages. As shown in Figure 2 , the application package can include an input method APP. In addition to this, the application package can also include camera, gallery, calendar, call, WLAN, Bluetooth, music, video, map, navigation, short message, etc.

[0095] The application framework layer provides application programming interfaces (APIs) and programming frameworks for the applications of the application layer. The application framework layer includes some pre-defined functions.

[0096] As shown in Figure 2 , in the embodiment of the present application, the application framework layer can include an input method manager service (IMMS), an input method service (IMS), and a temporary (temp) file management.

[0097] In the embodiments of the present application, the temporary file management is used to establish and manage the input method temporary file. The IMM, the IMMS and the IMS form a data transmission channel (hereinafter referred to as a data channel), and the input method APP can transmit data between the data channel and other modules, including but not limited to transmitting data between the data channel and the temporary file management.

[0098] In some embodiments not shown, the application framework layer can also include a window manager, a content provider, a view system, a phone manager, a resource manager, a notification manager, etc. The runtime includes a core library and a virtual machine. The Android runtime is responsible for the scheduling and management of the Android system.

[0099] The core library contains two parts: one part is the function function called by the java language, and the other part is the core library of Android.

[0100] The application layer and the application framework layer run in the virtual machine. The virtual machine executes the java file of the application layer and the application framework layer into a binary file. The virtual machine is used to manage the object life cycle, stack management, thread management, security and exception management, and garbage collection.

[0101] The system library can include multiple functional modules. For example: surface manager, media library, three-dimensional graphics processing library (for example: Open GLES), two-dimensional graphics engine (for example: SGL) and the like.

[0102] The kernel layer is the layer between hardware and software. The kernel layer at least contains display driver, camera driver, audio driver, sensor driver and the like.

[0103] Next, some terms in the present application are explained:

[0104] First, an application scenario of the present application is introduced, as shown in Figure 3 In the application scenario, the A user shoots the image of the environment where the A user is located by carrying a mobile phone.

[0105] Preview stream data: when the body of the A user enters the shooting posture, and holds the mobile phone and aims the camera of the mobile phone at the shooting object, but has not yet clicked the shooting button of the mobile phone, the camera of the mobile phone has actually been acquiring images in real time. These images are the preview stream data used to generate the preview image (that is, the image displayed before the processed result image of the mobile phone is displayed full screen) in the prior art.

[0106] Photo stream data: when the A user determines the picture to be taken by the mobile phone, the user clicks the photo button of the mobile phone, the camera captures a sequence of images about the picture, and the sequence of images is transmitted to the processor of the mobile phone, which is the photo stream data used to generate the processing result image.

[0107] Preview image: a large image displayed on the screen before the processing result image is displayed on the full screen of the mobile phone, that is, the large image first displayed on the screen of the mobile phone after the thumbnail is clicked.

[0108] Processing result image: the processor of the mobile phone takes the first frame image obtained by clicking the photo button as the reference frame, and takes the subsequent multiple images as the auxiliary, processes the image data of the multiple images based on the reference frame to obtain the image, which is the large image displayed on the screen of the mobile phone after the preview image.

[0109] With the continuous updating of terminal devices, in order to meet the needs of users to obtain high-quality images in multiple scenarios, manufacturers start from the image processing algorithm on the terminal device, so that the image processing algorithm on the updated terminal device is more and more complex. The problem brought by the complex algorithm is that it takes a long time to run these complex algorithms, so the terminal device takes a longer time to obtain the processing result image. From the perspective of the user, when the user takes a picture through his own mobile phone, he is eager to check the shooting effect to decide whether to take a new picture or continue to take other pictures. Due to the complexity of the image processing algorithm in the terminal device, the processing time of the shooting image is longer, so when the user finishes shooting and clicks the thumbnail (a small image displayed on the predetermined display position of the display screen of the terminal device) to check the shooting effect, the display interface of the mobile phone displays the preview image, which is in the loading state, and the image loading time may last for 3-5 seconds. The image loading time will be longer under the condition of full load or heavy load of the whole machine, so it is likely to exceed the patience limit time of the user, which brings the user a bad shooting experience, and further makes the user doubt the performance of the terminal device, which is not conducive to the sales of the terminal device by the manufacturer. Figure 5

[0110] In order to solve the above problem, the prior art generates a preview image according to the preview stream data for display, and waits for the processor of the terminal device to process the subsequent image sequence based on the initial image (reference frame) to obtain the processing result image, and then replaces the preview image with the processing result image. However, this brings the problem that when a moving object is photographed, the preview image and the processing result image are generated based on different reference frames, as shown in FIG. 4, Figure 4a the preview image generated by the prior art terminal device based on the preview stream data, Figure 4b ​The image is the processed result generated by the terminal device of the existing technology based on the image stream data. Figure 4a and Figure 4b It is known that the image displayed in the preview image is inconsistent with the image displayed in the processed result image. This causes a noticeable jump in the screen when the terminal device switches from displaying the preview image to displaying the processed result image, resulting in a poor photography experience for the user. Therefore, new technologies are urgently needed to solve this problem.

[0111] To address the aforementioned issues, this application proposes an image display method that generates a preview image using a reference frame for generating the processed result image. This method not only enables rapid generation of the preview image but also avoids or mitigates the problem of noticeable jumps during the process of switching the terminal device's display screen from showing the preview image to showing the processed result image.

[0112] For ease of understanding, the following embodiments of this application will be described using the following methods: Figure 1 and Figure 2 Taking a terminal device with the structure shown as an example, and using a smartphone as an example, the image display method provided in this application embodiment will be specifically described in conjunction with the accompanying drawings and application scenarios.

[0113] Figure 6 This is a schematic flowchart illustrating a video frame processing method according to an exemplary embodiment of this application. (Refer to...) Figure 6 As shown, the specific steps include:

[0114] Step S100: Obtain the initial image, which is a reference frame used to generate the processed result image.

[0115] In this process, after the user clicks the corresponding button on the terminal device, the terminal device captures at least one frame of image through its camera, typically four or six frames, which are used to generate the image stream data for processing. The initial image can be the first frame of the image stream data obtained by the terminal device, referred to as the reference frame below. Next, the image processor of the terminal device can process the reference frame according to an image processing algorithm, combining it with image data from other frames in the image stream data, to obtain the processed image.

[0116] It should be noted here that if the image captured by the terminal device's camera is a still image, then the image displayed in the reference frame and other multi-frame images in the image stream data can be consistent; however, if the image captured by the terminal device's camera is a moving image, then there will be situations where the image displayed in the reference frame and other multi-frame images in the image stream data are inconsistent.

[0117] For example, such as Figure 7As shown, A user collects a picture in B environment by a carried mobile phone, and obtains multiple frames of images about the picture. By Figure 7 It is known that A user collects a dynamic picture of a person running, so the images shown in the reference frame and the multiple frames of images in the other photographing stream data are inconsistent, but the processing result image is only required to be obtained by processing the reference frame (the first frame of image) by various image processing algorithms, and the preview image is also obtained by processing the reference frame, so as long as the picture of the preview image is consistent with the picture of the processing result image, even if the picture of each frame of image in the photographing stream data is inconsistent, the display effect of the terminal device will not be affected.

[0118] In step S200, the initial image is down-sampled according to a predetermined sampling rate to obtain a target image.

[0119] It is known that A user collects a dynamic picture of a person running, so the images shown in the reference frame and the multiple frames of images in the other photographing stream data are inconsistent, but the processing result image is only required to be obtained by processing the reference frame (the first frame of image) by various image processing algorithms, and the preview image is also obtained by processing the reference frame, so as long as the picture of the preview image is consistent with the picture of the processing result image, even if the picture of each frame of image in the photographing stream data is inconsistent, the display effect of the terminal device will not be affected.

[0120] Therefore, the present application can avoid or improve the screen jump problem mentioned above by processing the reference frame for generating the processing result image to obtain the preview image.

[0121] Specifically, after the terminal device can collect a plurality of frame image sequences by an image collection module such as a camera or a camera provided thereon, a first frame image (i.e. an initial image) can be selected from the plurality of frame image sequences and transmitted to an image processor provided in the terminal device, and then the initial image is down-sampled by the image processor according to a predetermined sampling rate (for example, 2 times, 6 times, 8 times, 12 times, etc.). The operation of down-sampling the initial image by the image processor once can not only obtain a target image, but also obtain a thumbnail corresponding to the target image, the preview image or the processing result image at the same time.

[0122] It should be noted that down-sampling is also called decimation, which is a common method of image processing. The principle of down-sampling is that for an image P with a size of MN, s times down-sampling is performed, i.e. an image with a size of (M / s)(N / s) is obtained, which can be understood as that the image in the s*s window of the initial image or S 2The value of the pixel point can be the mean value or the maximum value or a random value of all pixels in the window. s should be a common divisor of M and N. The initial image can be processed by a nearest neighbor sampling method, a quadratic interpolation method, a bicubic convolution method, etc. to achieve downsampling of the initial image to obtain the target image.

[0123] The initial image is processed by the downsampling technology to obtain the target image. The downsampling technology is simpler than various image processing algorithms for generating a processed image, and can reduce a lot of computation. Therefore, the initial image is processed by the downsampling technology to quickly obtain the preview image, avoid or improve the situation that the preview image is in image loading for a long time after the user clicks the thumbnail, and improve the user's shooting experience.

[0124] As shown in Figure 8a , the initial image is downsampled to obtain a thumbnail, and the thumbnail is displayed in the lower left corner of the mobile phone. Clicking the thumbnail, the terminal device can display the preview image on the large image floating layer through the display screen, as shown in Figure 8b , the preview image is displayed on the large image floating layer of the mobile phone.

[0125] In step S300, the noise in the target image is processed to obtain the preview image.

[0126] In the process of collecting the image sequence containing the initial image, the terminal device may be affected by factors such as the shooting environment and the performance of the camera in the terminal device, so that the collected image has noise, and the noise of the image will be more obvious when displayed on the high-brightness display screen of the terminal device. Noise, as the name implies, is unnecessary or redundant interference information in the target image. Various factors that interfere with people's reception of information in the image are all image noise. The noise in the target image, for example, is some random, discrete, isolated pixel points or pixel blocks that appear on the target image due to factors such as terminal device imaging sensor noise, photo grain noise, channel transmission error during image transmission, etc. These pixel points or pixel blocks are noise in the target image. Common image noise includes Gaussian noise, Poisson noise, multiplicative noise, salt and pepper noise, etc. In short, noise will make the image unclear. Therefore, in order to show the user a better quality, i.e. clearer preview image, the embodiments of the present application need to process the noise in the target image after obtaining the target image.

[0127] For example, the noise in the target image can be processed by mean filtering, median filtering, wavelet transform filtering, Wiener filtering, morphological filtering, etc.

[0128] The following embodiments of the present application will be described in detail on how to process the noise of the target image. Of course, the processing method of the noise of the target image can also have other methods, and the present application does not limit this.

[0129] In one embodiment, as shown in Figure 9 , Figure 9 An optional method embodiment for processing the noise in the target image to obtain a preview image is provided in the embodiments of the present application, and the method embodiment comprises the following steps:

[0130] Step S301, removing isolated pixel points of the target image by a median filtering method to obtain a first image.

[0131] In the embodiments of the present application, the isolated pixel points of the target image can be removed by the median filtering method to obtain the first image.

[0132] Most of the energy of the image is concentrated in the low and medium frequency bands of the amplitude spectrum, and in the higher frequency band, the information of interest is often overwhelmed by noise. Therefore, a filter that can reduce the amplitude of high frequency components can reduce the influence of noise.

[0133] Median filtering is a commonly used nonlinear smoothing filtering method. It is actually a kind of field operation, similar to convolution, but not weighted summation operation, but the pixels in the field are sorted by gray level, and then the middle value of the group is selected as the output pixel value. It can reduce or eliminate high frequency components in the Fourier space, but it affects low frequency components. Because the high frequency components correspond to the parts of the image where the gray value of the region edge has a large and fast change, the median filtering can filter out these high frequency components, making the image smoother.

[0134] The output pixel of the median filtering is determined by the middle value of the neighborhood image, so the median filtering is much less sensitive to extreme pixel values (pixels with large difference in gray value from surrounding pixels) than the average value, so it can eliminate isolated noise points and make the image less blurred. Its advantage is that it can protect the edge information of the image and remove the useless image noise contained in the image.

[0135] In one embodiment, as shown in Figure 10 , Figure 10 An optional method embodiment for removing isolated pixel points of the target image by a median filtering method to obtain a first image is provided in the embodiments of the present application, and the method embodiment comprises the following steps:

[0136] Step S3011, obtaining the gray value of all initial pixel points within the range of the two-dimensional template from the target image.

[0137] The two-dimensional template is actually a window moving up, down, left and right in the target image. The window is generally a square field, and the size of the window can be 3x3, 5x5, 7x7, etc. When the image processor in the terminal device roams in the target image according to the preset two-dimensional template, after a certain pixel point in the center of the target image coincides with the center of the two-dimensional template, all the pixel points in the two-dimensional template are all the initial pixel points mentioned in the embodiments of the present application, and then the gray values of all the pixel points are read in turn, for example, the two-dimensional template is a 3x3 matrix, and the gray values of the 9 pixel points are obtained.

[0138] In step S3012, the gray values of all the initial pixel points are sorted according to the arrangement order, and the gray value of the pixel point arranged in the middle is taken as the gray median value.

[0139] Based on the obtained gray values of all the pixel points, the gray values are sorted again, which can be from small to large or from large to small, and the gray value arranged in the middle is taken as the gray median value. For example, the image processor obtains the gray values of the 9 pixel points as {1, 4, 6, 8, 9, 12, 10, 15, 5}, and the number 9 is the gray median value.

[0140] In step S3013, based on the gray median value, each isolated pixel point in the target image is processed to obtain each target pixel point. The isolated pixel point refers to the pixel point in the center of the two-dimensional template.

[0141] The isolated pixel point is more in the target image, and the display is more serious in the case of high brightness on the screen of the terminal device, which greatly affects the visual effect of the target image.

[0142] Therefore, the gray value of each isolated pixel point can be assigned to the gray median value to remove the isolated points in the target image and obtain each target pixel point.

[0143] In step S3014, based on each target pixel point and each initial pixel point, a first image is obtained.

[0144] Further, after the isolated pixel points in the target image are processed according to the median filtering method to obtain each target pixel point, other pixel points remain unchanged, and a new image composed of other pixel points and each target pixel point is obtained, that is, a first image. For example, as shown in FIG. 11, Figure 11a is a target image with noise, Figure 11b is a first image obtained by median filtering through a 3x3 two-dimensional template. It can be seen that the first image after median filtering has less useless noise than the target image, and the first image is clearer.

[0145] In step S302, the first image is processed by the wavelet denoising method to obtain a preview image.

[0146] The median filtering method can only process isolated pixels in the target image. However, there are usually more than one kind of noise in the image, and the noise has a multi-faceted impact on the image. The noise affects the input, transmission, and output of the image, and thus reduces the resolution of the image and destroys the fine structure of the image, which brings inconvenience to the subsequent processing of the image (such as binarization operation and image feature extraction). Therefore, it is particularly important to suppress the noise and improve the signal-to-noise ratio of the image and highlight the application features of the image. Therefore, after the target image is processed by the median filtering method to obtain the first image, the first image is further processed by the wavelet denoising method.

[0147] The wavelet denoising method is based on the different distribution of noise and signal in the frequency domain. Generally, the signal is distributed in the low-frequency region, the noise is distributed in the high-frequency region, and the details of the image are also distributed in the high-frequency region. The wavelet denoising method has spatial and frequency limitations, has the property of multi-resolution analysis, can adapt to the local change of signal frequency, and can select respective thresholds on each wavelet decomposition layer to process the brightness noise and color noise in the first image to solve the problem of serious noise in the high-light scene.

[0148] In one embodiment, as shown in Figure 12 , Figure 12 An optional method embodiment for obtaining a preview image is provided in the embodiment of the present application, and the method embodiment includes the following steps:

[0149] In step S3021, the noise points in the first image are processed by the wavelet denoising method to obtain a second image.

[0150] In one embodiment, as shown in Figure 13 , Figure 13 An optional method embodiment for obtaining a second image is provided in the embodiment of the present application, and the method embodiment includes the following steps:

[0151] In step S30211, the first image is wavelet-decomposed to obtain respective detail components and respective approximation components. The detail component is the high-frequency part of the first image, and the approximation component is the low-frequency part of the first image.

[0152] The first image is processed by the wavelet denoising method. First, the first image is decomposed by the wavelet method. The wavelet denoising method is a time-frequency localization analysis method with changeable time window and frequency window. A wide time (space) window is used in the low-frequency part to analyze the slowly changing signal. A narrow time (space) window is used in the high-frequency part to accurately determine the position of the sudden signal. Therefore, the information in the first image can be adaptively extracted. The wavelet decomposition can be specifically performed as follows: selecting a wavelet base, and decomposing the first image by the Mallat fast algorithm to separate the high-frequency part and the low-frequency part of the first image.

[0153] In step S30212, each detail component is threshold quantized based on a predetermined threshold to obtain each quantized component.

[0154] Since the noise is usually contained in the high-frequency part, the high-frequency part obtained by the wavelet decomposition is further threshold processed. The wavelet coefficients greater than the threshold are considered as the transformation results of signals and noise, and if they are retained, the image details can be well maintained. The wavelet coefficients less than the threshold are considered as the transformation results of noise. The threshold denoising mainly includes a hard threshold algorithm and a soft threshold algorithm. The first image noise can be processed by the soft threshold algorithm in the embodiment of the present application. Specifically, the wavelet coefficients of the high-frequency part can be soft threshold processed based on a preset threshold. The wavelet coefficients greater than the threshold are retained, and the wavelet coefficients less than the threshold are removed to obtain the wavelet coefficients (i.e., each quantized component) after soft threshold processing.

[0155] In step S30213, each quantized component and each approximation component are wavelet reconstructed to obtain a second image.

[0156] Finally, the wavelet coefficients after soft threshold processing and the wavelet coefficients of the low-frequency part can be wavelet inverse transformed to realize wavelet reconstruction, and the second image is obtained.

[0157] In step S3022, a preview image is obtained based on the result of the smoothing processing of the second image.

[0158] Since the target object is only denoised by the above two methods, the noise processing requirement of the second image displayed under the screen display condition of the high-brightness / vibrant mode of the display screen of the terminal device cannot be met. Therefore, the second image needs to be further smoothed to obtain a preview image. The second image can be smoothed by an interpolation method, a current smoothing method, a convolution method, and the like, which are not limited in the present application.

[0159] The following, the embodiment of the application provides a kind of to the second image is carried out the method of smoothing processing, the method is for the phenomenon of different noise degree under different screen display conditions, using different fog degree processing mode to the second image is carried out to the image of denoising by different fog degree section.It is less than a certain threshold T3, then the fog degree of corresponding image under the fog scene of the second image is F3, using the Gaussian blur kernel of degree F3 to the image is carried out smoothing processing.

[0160] Specifically, referring to Figure 14 As shown in the figure, Figure 14 Another optional method embodiment for obtaining preview image is provided in the embodiment of the application, and the method embodiment includes the following steps:

[0161] In step S30221, the light sensitivity data when the terminal device collects the initial image is obtained.

[0162] Wherein, after the initial image is collected by the image collection module such as camera in terminal device, the light sensitivity data of terminal device can be determined according to the parameters of initial image, or the parameters of camera at this time in terminal device can be directly obtained to obtain the light sensitivity data, which is not limited.

[0163] In step S30222, the image blur degree corresponding to the light sensitivity data is determined based on the light sensitivity data and the corresponding relationship information; the corresponding relationship information includes a plurality of light sensitivity data and the image blur degree corresponding to the plurality of light sensitivity data.

[0164] Wherein, the corresponding relationship information of light sensitivity data and image blur degree corresponding to light sensitivity data can be pre-set in terminal device, for example: light sensitivity <= T1, corresponding image blur degree is F1; light sensitivity <= T2, corresponding image blur degree is F2; light sensitivity <= T3, corresponding image blur degree is F3; light sensitivity <= T4, corresponding image blur degree is F4, etc.

[0165] Once the light sensitivity data when the terminal device collects the initial image is obtained, the corresponding image blur degree can be quickly determined by looking up the corresponding relationship information, so as to improve the processing efficiency of image, and to show the preview image to the user faster.

[0166] In step S30223, the second image is smoothed based on the image blur degree by Gaussian blur algorithm, and the preview image is obtained.

[0167] The Gaussian blur algorithm is an algorithm for applying a normal distribution to image noise reduction processing. The so-called "blurring" can be understood as taking the average of the surrounding pixels for each pixel, that is, the "intermediate pixel point" takes the average of the "surrounding points". Numerically, this is a kind of "smoothing". On the image, it is equivalent to producing a "blurring effect", and the "intermediate point" loses details. When calculating the average, the larger the value range, the stronger the "blurring effect". When performing image blurring, the average of each pixel point in the second image is taken. If a simple average is used, it is obviously unreasonable because the image is continuous, and the closer the pixel points, the closer the relationship, and the farther the pixel points, the more distant the relationship. Therefore, the average is often calculated by a weighted average method, and the normal distribution is obviously a desirable weight distribution pattern.

[0168] On the image, the normal distribution is a bell-shaped curve, the closer to the center, the larger the value, and the farther from the center, the smaller the value. When calculating the average, only the "center pixel point" is taken as the origin, and other pixel points are assigned weights according to their positions on the normal curve to obtain a weighted average. The normal distribution is one-dimensional, and the image is two-dimensional, so a two-dimensional normal distribution is needed. The density function of the normal distribution is called the "Gaussian function". The two-dimensional Gaussian function can be derived from the one-dimensional Gaussian function, and the weight of each pixel point can be calculated by the two-dimensional Gaussian function. Further, according to the set weight matrix, assuming that the second image has 9 pixel points, the gray value of each pixel point is determined, and then the respective gray value is multiplied by the respective weight value to obtain a new gray value matrix. Adding up the gray values is the Gaussian blur value of the center pixel point. Repeating the above process for all pixel points, the preview image processed by the Gaussian blur algorithm is obtained.

[0169] The embodiment of the present application reversely calculates the gray value of each pixel point according to the known image blur degree, and then assigns the gray value of each pixel point to the calculated gray value, thereby completing the processing of the second image and obtaining the preview image.

[0170] It should be noted that if the camera of the terminal device captures multiple images, the noise of the reference frame can be processed based on the noise information of the subsequent multiple images to obtain a preview image with better preview effect.

[0171] Step S400: displaying the preview image at the preview display position.

[0172] After obtaining the preview image according to the above process, the preview image can be displayed in the corresponding area of the display screen of the terminal device. For example, as shown in Figure 8b the terminal device is a mobile phone, and the preview image is displayed on the entire interface of the mobile phone, that is, the preview display position behind.

[0173] Step S500, processing the image sequence containing the initial image through an image processing algorithm to obtain a processed result image.

[0174] The image sequence is a plurality of images collected by an image collection module such as a camera or a camera of the terminal device, and the image sequence includes the initial image, that is, the first frame of image in the image sequence. The image sequence can include only the initial image, or can include 4 images, or can include 6 images, which are not limited in the present application. Based on the obtained initial image, the image sequence containing the initial image can be processed through a high-multiplication synthesis super-clear algorithm, ZSL front-end frame extraction, and the like to obtain a processed result image.

[0175] Step S600, replacing the preview image displayed at the preview display position with the processed result image.

[0176] The terminal device can switch the preview image displayed on the display screen to the processed result image for display after the user clicks the thumbnail. Since the preview image and the processed result image are both obtained based on the reference frame processing, only the processing method is different, so there is no obvious jump in the process of switching the display screen from displaying the preview image to displaying the processed result image. For example, as shown in Figure 15a , the user A clicks the thumbnail, and the display screen of the mobile phone displays the preview image. After the image processor processes the reference frame to obtain the processed result image, the preview image is switched to the processed result image for display, as shown in Figure 15b .

[0177] Next, as shown in Figure 16 , the technical solution of the present application is described in detail in one exemplary embodiment of the present application:

[0178] Step S1601, the user A collects 4 or 6 images through the camera of the mobile phone, and the image processor in the mobile phone obtains the first frame of image from the 4 or 6 images as the initial image.

[0179] Step S1602, the image processor performs down-sampling on the initial image through the set sampling rate to obtain a target image, and obtains the gray values of all initial pixel points within the two-dimensional template range from the target image.

[0180] Step S1603, the image processor sorts the gray scale values of all the initial pixel points according to the arrangement order, takes the gray scale value of the initial pixel point arranged in the middle as the gray scale median value, assigns the gray scale value of each isolated pixel point as the gray scale median value, obtains each target pixel point, and obtains the first image in combination with each initial pixel point;

[0181] Step S1604, the image processor performs wavelet decomposition on the first image to obtain each detail component and each approximation component, performs threshold quantization processing on each detail component based on a predetermined threshold to obtain each quantized component, and performs wavelet reconstruction on each quantized component and each approximation component to obtain the second image;

[0182] Step S1605, the image processor obtains the light sensitivity data T1 when the terminal device collects the initial image, determines the image blurring degree F1 corresponding to the light sensitivity data T1 based on the light sensitivity data and the corresponding relationship information stored in the memory, processes the blurring degree of the second image to match F1 through the Gaussian blurring algorithm, obtains the preview image, and displays the preview image in full screen after the user A clicks the thumbnail.

[0183] Step S1606, the image processor obtains the foreground, background, size, resolution, noise, blurring degree and other data of the other images except the initial image from the 4 or 6 images, processes the initial image to obtain a processing result image, and finally switches the preview image displayed on the mobile phone display screen to the processing result image.

[0184] It should be understood that, although each step in the flowchart involved in each embodiment as described above is displayed in sequence according to the arrow, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least part of the steps in the flowchart involved in each embodiment as described above can include multiple steps or stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be executed in rotation or alternation with at least part of other steps or steps or stages in other steps.

[0185] Based on the same inventive concept, the embodiments of the present application also provide an image display device for implementing the image display method described above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so the specific limitations in one or more image display device embodiments provided below can refer to the limitations of the image display method in the above text, which will not be described here.

[0186] In one embodiment, as Figure 17As shown, an image display device 1700 is provided, which includes an acquisition module 1701, a sampling module 1702, a processing module 1703, and a display module 1704,

[0187] The acquisition module 1701 is configured to acquire an initial image, the initial image being a reference frame for generating a processed result image;

[0188] The sampling module 1702 is configured to down-sample the initial image according to a predetermined sampling rate to obtain a target image;

[0189] The processing module 1703 is configured to process noise in the target image to obtain a preview image;

[0190] The display module 1704 is configured to display the preview image at a preview display position;

[0191] The processing module 1703 is further configured to process an image sequence containing the initial image by using an image processing algorithm to obtain a processed result image;

[0192] The display module 1704 is further configured to replace the preview image displayed at the preview display position with the processed result image.

[0193] In one embodiment, the processing module 1703 is specifically configured to perform isolated pixel point removal processing on the target image by using a median filtering method to obtain a first image; and perform noise reduction processing on the first image by using a wavelet denoising method to obtain the preview image.

[0194] In one embodiment, the processing module 1703 is specifically further configured to acquire, from the target image, gray scale values of all initial pixel points within a two-dimensional template range; sort the gray scale values of all the initial pixel points according to an arrangement order, and take the gray scale value of an initial pixel point arranged in the middle as a gray scale median value; process each isolated pixel point in the target image based on the gray scale median value to obtain each target pixel point, the isolated pixel point being an initial pixel point at a center position of the two-dimensional template; and obtain the first image based on each target pixel point and each initial pixel point.

[0195] In one embodiment, the processing module 1703 is specifically further configured to assign the gray scale value of each isolated pixel point to the gray scale median value to obtain each target pixel point.

[0196] In one embodiment, the processing module 1703 is specifically further configured to process noise points in the first image by using a wavelet denoising method to obtain a second image; and obtain the preview image based on a result of smoothing processing on the second image.

[0197] In an embodiment, the processing module 1703 is further configured to perform wavelet decomposition on the first image to obtain respective detail components and respective approximation components, the detail components being high frequency parts in the first image, and the approximation components being low frequency parts in the first image; perform threshold quantization processing on the respective detail components based on a predetermined threshold to obtain respective quantized components; and perform wavelet reconstruction on the respective quantized components and the respective approximation components to obtain the second image.

[0198] In an embodiment, the processing module 1703 is further configured to obtain light sensitivity data when the terminal device collects the initial image; determine the image blurriness corresponding to the light sensitivity data based on the light sensitivity data and the correspondence relationship information; the correspondence relationship information includes a plurality of light sensitivity data and image blurriness corresponding to the plurality of light sensitivity data; and perform smoothing processing on the second image based on the image blurriness by using a Gaussian blur algorithm to obtain the preview image.

[0199] The above-mentioned modules in the image display can be all or partially implemented by software, hardware, and combinations thereof. The above-mentioned modules can be embedded in or independent of a processor in the computer device in a hardware form, or stored in a memory in the computer device in a software form, so as to be called and executed by a processor to perform operations corresponding to the above-mentioned modules.

[0200] Those skilled in the art can understand that Figure 17 The skilled in the art can understand that

[0201] In an embodiment, a computer device is provided, which can be a terminal device, and an internal structure diagram of the computer device can be as shown in FIG. 10. Figure 18The computer device includes a processor, a memory, a communication interface, a display screen, a receiver, a transmitter and an input device connected by a system bus. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The communication interface, the transmitter and the receiver of the computer device are configured to communicate with an external server in a wired or wireless manner. The wireless manner can be achieved by WIFI, an operator network, NFC (Near Field Communication) or other technologies. The computer program is executed by the processor to implement a dynamic password generation method. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen. The input device of the computer device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the computer device, or an external keyboard, touchpad or mouse, etc.

[0202] In one embodiment, a terminal device is provided, including a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0203] An initial image is obtained, which is a reference frame for generating a processing result image;

[0204] The initial image is down-sampled according to a predetermined sampling rate to obtain a target image;

[0205] The noise in the target image is processed to obtain a preview image;

[0206] The preview image is displayed at a preview display position;

[0207] An image sequence including the initial image is processed by an image processing algorithm to obtain a processing result image;

[0208] The preview image displayed at the preview display position is replaced by the processing result image.

[0209] In one embodiment, the processor further implements the following steps when executing the computer program:

[0210] The target image is processed by a median filtering method to remove isolated pixel points to obtain a first image; the first image is processed by a wavelet denoising method to obtain a preview image.

[0211] In one embodiment, the processor further implements the following steps when executing the computer program:

[0212] Acquire gray scale values of all initial pixel points in the range of the two-dimensional template from the target image; sort the gray scale values of all initial pixel points according to the arrangement order, and take the gray scale value of the initial pixel point arranged in the middle as the gray scale median value; process each isolated pixel point in the target image based on the gray scale median value to obtain each target pixel point, the isolated pixel point being the initial pixel point at the center position of the two-dimensional template; and obtain the first image based on each target pixel point and each initial pixel point.

[0213] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0214] Assign the gray scale value of each isolated pixel point to the gray scale median value to obtain each target pixel point.

[0215] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0216] Process the noise points in the first image by the wavelet denoising method to obtain a second image; and obtain the preview image based on the result of the smoothing processing on the second image.

[0217] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0218] Wavelet-decompose the first image to obtain each detail component and each approximation component, the detail component being the high-frequency part of the first image and the approximation component being the low-frequency part of the first image; perform threshold quantization processing on each detail component based on a predetermined threshold to obtain each quantized component; and perform wavelet reconstruction on each quantized component and each approximation component to obtain the second image.

[0219] In one embodiment, the processor, when executing the computer program, also implements the following steps:

[0220] Acquire the light sensitivity data when the terminal device collects the initial image; determine the image blur degree corresponding to the light sensitivity data based on the light sensitivity data and the corresponding relationship information, the corresponding relationship information including a plurality of light sensitivity data and the image blur degrees corresponding to the plurality of light sensitivity data; and perform smoothing processing on the second image by the Gaussian blur algorithm based on the image blur degree to obtain the preview image.

[0221] In one embodiment, a computer readable storage medium is provided, which stores a computer program, and the computer program, when executed by a processor, implements the following steps:

[0222] Acquire an initial image, the initial image being a reference frame for generating a processing result image;

[0223] Down-sample the initial image according to a predetermined sampling rate to obtain a target image;

[0224] Process the noise in the target image to obtain a preview image;

[0225] Display the preview image at a preview display position;

[0226] Process an image sequence containing the initial image through an image processing algorithm to obtain a processing result image;

[0227] Replace the preview image displayed at the preview display position with the processing result image.

[0228] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0229] Process the target image through a median filtering method to remove isolated pixel points to obtain a first image; and process the first image through a wavelet denoising method to obtain a preview image.

[0230] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0231] Obtain the gray scale values of all initial pixel points within a two-dimensional template range from the target image; sort the gray scale values of all initial pixel points according to the arrangement order, and take the gray scale value of the initial pixel point arranged in the middle as a gray scale median value; process each isolated pixel point in the target image based on the gray scale median value to obtain each target pixel point, wherein the isolated pixel point refers to the initial pixel point at the center position of the two-dimensional template; and obtain a first image based on each target pixel point and each initial pixel point.

[0232] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0233] Assign the gray scale value of each isolated pixel point to the gray scale median value to obtain each target pixel point.

[0234] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0235] Process the noise points in the first image through a wavelet denoising method to obtain a second image; and obtain a preview image based on the result of smoothing processing of the second image.

[0236] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0237] Wavelet-decompose the first image to obtain each detail component and each approximation component, wherein the detail component is the high-frequency part of the first image, and the approximation component is the low-frequency part of the first image; perform threshold quantization processing on each detail component based on a predetermined threshold to obtain each quantized component; and perform wavelet reconstruction on each quantized component and each approximation component to obtain a second image.

[0238] In one embodiment, the computer program, which is executed by a processor, further implements the following steps:

[0239] Obtaining the sensitivity data when the terminal device collects the initial image; determining the image blur corresponding to the sensitivity data based on the sensitivity data and the corresponding relationship information; the corresponding relationship information includes a plurality of sensitivity data and the image blur corresponding to the plurality of sensitivity data; performing smoothing processing on the second image based on the image blur through the Gaussian blur algorithm to obtain the preview image.

[0240] In one embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the following steps:

[0241] Obtaining an initial image, the initial image being a reference frame for generating a processing result image;

[0242] Down-sampling the initial image according to a predetermined sampling rate to obtain a target image;

[0243] Processing the noise in the target image to obtain a preview image;

[0244] Displaying the preview image at a preview display position;

[0245] Processing an image sequence containing the initial image through an image processing algorithm to obtain a processing result image;

[0246] Replacing the preview image displayed at the preview display position with the processing result image.

[0247] In one embodiment, the computer program, which is executed by a processor, further implements the following steps:

[0248] Performing processing to remove isolated pixel points on the target image through a median filtering method to obtain a first image; performing noise reduction processing on the first image based on a wavelet denoising method to obtain a preview image.

[0249] In one embodiment, the computer program, which is executed by a processor, further implements the following steps:

[0250] Obtaining the gray scale values of all initial pixel points within a two-dimensional template range from the target image; sorting the gray scale values of all initial pixel points according to the arrangement order, and taking the gray scale value of the initial pixel point arranged in the middle as the gray scale median value; processing each isolated pixel point in the target image based on the gray scale median value to obtain each target pixel point, the isolated pixel point being the initial pixel point at the center position of the two-dimensional template; obtaining a first image based on each target pixel point and each initial pixel point.

[0251] In one embodiment, the computer program, which is executed by a processor, further implements the following steps:

[0252] The gray value of each isolated pixel point is assigned as a gray value median, and each target pixel point is obtained.

[0253] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0254] The noise points in the first image are processed by a wavelet denoising method to obtain a second image; and based on a result of smoothing processing on the second image, a preview image is obtained.

[0255] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0256] The first image is wavelet-decomposed to obtain each detail component and each approximation component, the detail component being a high-frequency part in the first image, and the approximation component being a low-frequency part in the first image; each detail component is threshold-quantized based on a predetermined threshold to obtain each quantized component; and each quantized component and each approximation component are wavelet-reconstructed to obtain a second image.

[0257] In one embodiment, the computer program, when executed by the processor, further implements the following steps:

[0258] Sensitivity data when the terminal device collects an initial image is obtained; based on the sensitivity data and correspondence relationship information, image blurriness corresponding to the sensitivity data is determined, the correspondence relationship information including a plurality of sensitivity data and image blurriness corresponding to the plurality of sensitivity data; and based on the image blurriness, the second image is smoothed by a Gaussian blur algorithm to obtain a preview image.

[0259] It is easy to understand that, on the basis of the several embodiments provided in the present application, the skilled in the art can combine, split, recombine, etc. the embodiments of the present application to obtain other embodiments, and these embodiments do not exceed the protection scope of the present application.

[0260] The above detailed description of the specific embodiments of the present application has further detailed the purposes, technical solutions and beneficial effects of the embodiments of the present application. It should be understood that the above is only a specific embodiment of the present application, and is not used to limit the protection scope of the embodiments of the present application. Any modification, equivalent replacement, improvement, etc. made on the basis of the technical solutions of the embodiments of the present application should be included in the protection scope of the embodiments of the present application.

Claims

1. An image display method characterized by, The method is performed on a terminal device, and the method comprises: obtaining an initial image, the initial image being a reference frame for generating a processing result image; the initial image being a first frame image in an image sequence included in streaming data; down-sampling the initial image according to a predetermined sampling ratio to obtain a target image; processing noise in the target image to obtain a preview image; displaying the preview image at a preview display position; processing the image sequence based on the initial image as a reference frame by using an image processing algorithm to obtain the processing result image; replacing the preview image displayed at the preview display position with the processing result image; wherein processing noise in the target image to obtain a preview image comprises: processing the target image to remove isolated pixel points by using a median filtering method to obtain a first image; processing noise points in the first image by using a wavelet denoising method to obtain a second image; obtaining light sensitivity data of the terminal device when the initial image is captured; determining image blur corresponding to the light sensitivity data based on the light sensitivity data and corresponding relationship information; the corresponding relationship information comprising a plurality of light sensitivity data and image blur corresponding to the plurality of light sensitivity data; the image blur being used to represent the size of a Gaussian blur kernel; performing smoothing processing on the second image by using a Gaussian blur algorithm based on the image blur to obtain the preview image.

2. The method of claim 1, wherein, The processing of the target image to remove isolated pixel points by using a median filtering method to obtain a first image comprises: obtaining the gray scale values of all initial pixel points within a two-dimensional template range from the target image; sorting the gray scale values of all initial pixel points according to an arrangement order, and taking the gray scale value of the initial pixel point arranged in the middle as a gray scale median value; processing each isolated pixel point in the target image based on the gray scale median value to obtain each target pixel point, the isolated pixel point being an initial pixel point at the center position of the two-dimensional template; obtaining the first image based on each target pixel point and each initial pixel point.

3. The method of claim 2, wherein, The processing of each isolated pixel point in the target image based on the gray scale median value to obtain each target pixel point comprises: assigning the gray scale value of each isolated pixel point to the gray scale median value to obtain each target pixel point.

4. The method of claim 1, wherein, The processing of noise points in the first image by using a wavelet denoising method to obtain a second image comprises: performing wavelet decomposition on the first image to obtain each detail component and each approximation component, the detail component being a high-frequency part of the first image, and the approximation component being a low-frequency part of the first image; performing threshold quantization processing on each detail component based on a predetermined threshold to obtain each quantized component; performing wavelet reconstruction on each quantized component and each approximation component to obtain the second image.

5. An image display device, characterized by comprising: The apparatus comprises: an obtaining module configured to obtain an initial image, the initial image being a reference frame for generating a processing result image; the initial image being a first frame image in an image sequence included in streaming data; sampling module, configured to down-sample the initial image according to a predetermined sampling rate to obtain a target image; processing module, configured to process noise in the target image to obtain a preview image; display module, configured to display the preview image at a preview display position; the processing module is further configured to process the image sequence based on the initial image as a reference frame by using an image processing algorithm to obtain the processing result image; the display module is further configured to replace the preview image displayed at the preview display position with the processing result image; the processing module is specifically configured to: perform isolated pixel point removal processing on the target image by using a median filtering method to obtain a first image; perform noise point processing on the first image by using a wavelet denoising method to obtain a second image; obtain light sensitivity data when the initial image is captured; determine image blur corresponding to the light sensitivity data based on the light sensitivity data and corresponding relationship information; the corresponding relationship information includes a plurality of light sensitivity data and image blur corresponding to the plurality of light sensitivity data; the image blur is used to represent the size of a Gaussian blur kernel; perform smoothing processing on the second image by using a Gaussian blur algorithm based on the image blur to obtain the preview image.

6. A terminal device, characterized by comprising: a processor and a memory for storing executable instructions of the processor; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the steps of the image display method according to any one of claims 1 to 4.

7. A computer-readable storage medium having stored thereon a computer program, characterized in that the computer program is executed by the processor to implement the steps of the image display method according to any one of claims 1 to 4.

8. A computer program product comprising a computer program, characterized in that, the computer program is executed by the processor to implement the steps of the image display method according to any one of claims 1 to 4. the computer program is executed by the processor to implement the steps of the image display method according to any one of claims 1 to 4.

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