CN109712097B - Image processing method, image processing device, storage medium and electronic equipment - Google Patents
Image processing method, image processing device, storage medium and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application discloses an image processing method, an image processing device, a storage medium and electronic equipment. The method comprises the following steps: the method comprises the steps of obtaining an image to be processed, carrying out image decomposition on the image to be processed to obtain a second decomposition image and a first decomposition image carrying image brightness information, carrying out brightness adjustment on the first decomposition image to generate a first adjustment image, and carrying out image fusion on the first adjustment image and the second decomposition image to generate a first processing image. By adopting the technical scheme, the first decomposition image carrying the image brightness information is decomposed from the processed image, brightness of the first decomposition image is adjusted in a targeted manner, under the condition that other characteristic parameters of the image are not influenced, the image brightness is improved, the data processing amount is reduced, and the image processing efficiency and the image processing effect are improved.
Description
Technical Field
The embodiment of the application relates to the technical field of electronic equipment, in particular to an image processing method, an image processing device, a storage medium and electronic equipment.
Background
With the continuous development of electronic devices such as mobile phones and tablet computers, more and more photographing functions of the electronic devices are widely used by users, and the requirements of the users on the photographing performance of the electronic devices are higher and higher.
In order to improve image quality, after an image is captured by an electronic device, the image is often subjected to image enhancement or brightening, and image processing algorithms such as histogram equalization and wavelet transformation image enhancement algorithms are generally adopted.
Disclosure of Invention
The embodiment of the application provides an image processing method, an image processing device, a storage medium and an electronic device, and improves image processing quality.
In a first aspect, an embodiment of the present application provides an image processing method, including:
acquiring an image to be processed, and performing image decomposition on the image to be processed to obtain a second decomposed image and a first decomposed image carrying image brightness information;
adjusting the brightness of the first decomposition image to generate a first adjustment image;
and carrying out image fusion on the first adjustment image and the second decomposition image to generate a first processing image.
In a second aspect, an embodiment of the present application provides an image processing apparatus, including:
the image decomposition module is used for acquiring an image to be processed and decomposing the image to be processed to obtain a second decomposed image and a first decomposed image carrying image brightness information;
the brightness adjusting module is used for adjusting the brightness of the first decomposed image to generate a first adjusted image;
and the image fusion module is used for carrying out image fusion on the first adjustment image and the second decomposition image and generating a first processing image.
In a third aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements an image processing method according to the present application.
In a fourth aspect, an embodiment of the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements an image processing method according to an embodiment of the present application when executing the computer program.
According to the image processing method provided by the embodiment of the application, the image to be processed is subjected to image decomposition to obtain a second decomposition image and a first decomposition image carrying image brightness information, the brightness of the first decomposition image is adjusted to generate a first adjustment image, and the first adjustment image and the second decomposition image are subjected to image fusion to generate the first processing image. By adopting the scheme, the first decomposition image carrying the image brightness information is decomposed from the processed image, and brightness adjustment is performed on the first decomposition image in a targeted manner, so that under the condition of not influencing other characteristic parameters of the image, the image brightness is improved, the data processing amount is reduced, and the image processing efficiency and the image processing effect are improved.
Drawings
Fig. 1 is a schematic flowchart of an image processing method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another image processing method according to an embodiment of the present application;
fig. 3 is a schematic flowchart of another image processing method according to an embodiment of the present application;
fig. 4 is a schematic flowchart of another image processing method according to an embodiment of the present application;
fig. 5 is a schematic flowchart of another image processing method according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an image processing apparatus according to an embodiment of the present application;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of another electronic device according to an embodiment of the present application.
Detailed Description
The technical scheme of the application is further explained by the specific implementation mode in combination with the attached drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Fig. 1 is a flowchart of an image processing method provided in an embodiment of the present application, where the method may be executed by an image processing apparatus, where the apparatus may be implemented by software and/or hardware, and may be generally integrated in an electronic device. As shown in fig. 1, the method includes:
And 102, adjusting the brightness of the first decomposed image to generate a first adjusted image.
And 103, carrying out image fusion on the first adjustment image and the second decomposition image to generate a first processing image.
For example, the electronic device in the embodiment of the present application may include smart devices such as a mobile phone, a tablet computer, and a camera.
The image to be processed may be acquired in real time by an image acquisition module (e.g., a camera) of the electronic device, or may be a local image stored in the electronic device. The image decomposition is used for decomposing an image to be processed into two or more images comprising different image characteristic parameters, the decomposed images obtained by different image decomposition modes are different, the image decomposition mode can be determined according to the requirements of the decomposed images, the requirements of the decomposed images can be that the decomposed images comprise the characteristic parameters to be processed and the characteristic parameters to be protected, in the embodiment, the image to be processed is decomposed into two decomposed images respectively carrying the two characteristic parameters, the two decomposed images can be respectively processed, and the processing processes of the two characteristic parameters are independent from each other and do not interfere with each other; or only one of the decomposition images is processed, the characteristic parameters of the other decomposition image are kept, and the characteristic parameters of the other decomposition image are not influenced in the image processing process, so that the image processing quality is improved.
In this embodiment, the purpose of image decomposition is to decompose a decomposed image containing luminance information from an image to be processed, and the image decomposition manner and the number and type of second decomposed images are not limited herein. For example, the image decomposition method in the present embodiment may be, but is not limited to, intrinsic decomposition (MCA), Morphological Component Analysis (MCA), or the like. For example, the image decomposition may be performed on the image based on a neural network model with an image decomposition function, and the acquired image to be processed is transmitted to a pre-trained neural network model, so as to obtain a first decomposed image and a second decomposed image. The neural network model can be a lightweight neural network model, can be configured in electronic equipment such as a mobile phone and a camera, and simultaneously ensures higher image decomposition precision.
The first decomposition image carrying the image brightness information is obtained through image decomposition, brightness adjustment is carried out on the first decomposition image, pertinence is strong, the calculated amount is small, the second decomposition image is kept while the brightness adjustment is carried out on the image to be processed, and the influence of characteristic parameters in the second decomposition image in the brightness adjustment process is avoided. And carrying out image fusion on the first adjustment image and the second decomposition image obtained by brightness adjustment to obtain a first processing image, wherein the image fusion mode is determined according to the image decomposition mode, and the image fusion mode is the reverse process of the image decomposition mode.
In this embodiment, the brightness adjustment of the first decomposition image may be to determine a brightness adjustment manner according to a scene of the image to be processed, and may exemplarily be to perform scene recognition on the image to be processed when the processed image is acquired, and determine the brightness adjustment manner according to a scene recognition result, where the image scene may include, but is not limited to, a landscape scene, a portrait scene, a sunset scene, a night scene, a backlight scene, a food scene, and the like. The electronic device may store standard brightness distribution of each image scene, call the corresponding standard brightness distribution according to the scene recognition result, and adjust the brightness distribution in the first decomposed image according to the standard brightness distribution to realize brightness adjustment of the image to be processed. Optionally, when a face exists in the image to be processed, the face region may be segmented, and different brightness adjustments may be performed on the face region and the background region, respectively, so as to improve the pertinence of brightness adjustment and the processing effect of the face region.
The image processing method provided in the embodiment of the application obtains an image to be processed, performs image decomposition on the image to be processed to obtain a second decomposition image and a first decomposition image carrying image brightness information, performs brightness adjustment on the first decomposition image to generate a first adjustment image, and performs image fusion on the first adjustment image and the second decomposition image to generate a first processing image. By adopting the scheme, the first decomposition image carrying the image brightness information is decomposed from the processed image, and brightness adjustment is performed on the first decomposition image in a targeted manner, so that under the condition of not influencing other characteristic parameters of the image, the image brightness is improved, the data processing amount is reduced, and the image processing efficiency and the image processing effect are improved.
Fig. 2 is a schematic flow chart of another image processing method according to an embodiment of the present disclosure, and referring to fig. 2, the method according to the embodiment includes the following steps:
And 204, processing each brightness value according to the gain value to generate a first adjusting image.
And step 205, performing image fusion on the first adjustment image and the reflection component image to generate a first processed image.
In this embodiment, an image to be processed is decomposed into a shadow component image and a reflection component image in an intrinsic decomposition manner, where the shadow component image includes information such as an illumination condition of an image scene and a shading effect, shadow, shielding and the like caused by a geometric structure, the shadow component image is a grayscale image, and a grayscale value of each pixel point represents a brightness value of each pixel point; the reflection component image shows the correspondence of the reflectivity of the object material in the image in each frequency band, and is a color image.
And traversing the brightness values of all the pixel points of the shadow component image to generate the brightness distribution of the shadow component image, wherein the brightness distribution can be the number of the pixel points including all the brightness values or the proportion of the number of the pixel points of all the brightness values to the total number of the pixel points, and can be displayed in a histogram mode. And determining a gain rule according to the brightness distribution of the shadow component image, wherein the gain rule can be shown in the form of a gain curve and comprises the corresponding relation between the brightness value and the gain. Illustratively, the brightness value is segmented, and the gain rule is determined according to the pixel point proportion of each segmented brightness. For example, segmenting the luminance value may be segmenting the luminance value of the image to be processed according to a luminance mean value, specifically, determining the luminance mean value according to the luminance distribution of the shadow component image, dividing the luminance value larger than the luminance mean value into a luminance range, and dividing the luminance value smaller than the luminance mean value into a luminance range; the luminance values may also be divided into a plurality of luminance ranges according to a predetermined segmentation manner, such as 0-50, 51-100, 101-. The corresponding relationship between the brightness value and the gain in the gain rule may be a one-to-one corresponding relationship between each brightness value and the gain, or a corresponding relationship between a brightness range and the gain. Illustratively, the gain rule may be, but is not limited to, an S-shaped curve. Optionally, the gain rule may also be determined according to the image scene. And determining a gain rule (gain curve) according to the scene standard brightness distribution of the image to be processed and the brightness distribution of the shadow component image.
In this embodiment, the gain of each pixel point is determined by the brightness value and the gain rule of each pixel point, and the brightness of the shadow component image is adjusted to generate a first adjusted image. Optionally, a brightness range to which the brightness value of each pixel belongs may be determined, the gain of each pixel is determined according to the brightness range and the gain rule, and the brightness of the shadow component image is adjusted to generate a first adjusted image.
Optionally, the method further includes: determining whether each processed brightness value is larger than the maximum value of the brightness range; and if so, adjusting the brightness value larger than the maximum value of the brightness range to be the maximum value of the brightness range. In this embodiment, since the luminance value range of the pixel point is 0-255, when the gained luminance value is greater than 255, it indicates that the adjusted luminance value does not conform to the luminance range, and the luminance value is adjusted to the maximum value of the luminance range, that is, 255, the problem that the luminance value in the adjusted shadow component image exceeds the range is avoided, and the luminance adjustment effect of the image to be processed is improved. The brightness value obtained after processing may be judged after processing each brightness value according to the gain value, or after determining the gain value of each brightness value and before brightness processing, the judgment may be performed based on the gain value and the original brightness value, and if it is determined that the processed brightness value is greater than the maximum brightness range value, the processed brightness value is directly determined as the maximum brightness range value, so that secondary adjustment of the brightness value is not required, and the image processing efficiency is improved.
The image processing method provided in the embodiment of the application obtains the shadow component image composed of pure brightness values by essentially decomposing the image to be processed, determines the gain rule for brightness adjustment of the shadow component image, determines the brightness gain of each pixel point, and adjusts the brightness of each pixel point, thereby avoiding influencing other characteristic parameters of the image to be processed, having strong pertinence of brightness adjustment, high efficiency, and improving the image processing quality and efficiency.
Fig. 3 is a schematic flow chart of another image processing method provided in an embodiment of the present application, where the present embodiment is an alternative to the foregoing embodiment, and accordingly, as shown in fig. 3, the method of the present embodiment includes the following steps:
301, acquiring an image to be processed, and performing essential decomposition on the image to be processed to obtain a reflection component image and a shadow component image carrying image brightness information.
And 304, processing each brightness value according to the gain value to generate a first adjusting image.
And 305, performing saturation enhancement processing on the reflection component image to generate a second adjustment image.
And step 306, performing image fusion on the first adjustment image and the second adjustment image to generate a first processing image.
In this embodiment, on the basis of performing brightness adjustment on the shadow component image, color saturation adjustment is performed on the reflection component image to reflect the color saturation of the component image, and further, image fusion is performed on the shadow component image after brightness adjustment and the reflection component image after color saturation adjustment to realize adjustment of the brightness and the color saturation of the image to be processed. Meanwhile, because the shadow component image and the reflection component image are independent of each other, and the brightness adjusting process and the color saturation adjusting process are independent of each other and do not interfere with each other, the pertinence of brightness and color saturation adjustment is improved.
In some embodiments, performing saturation enhancement processing on the second decomposed image to generate a second adjusted image comprises: acquiring three-channel color information of any pixel point in the second decomposition image; for any pixel point, determining a three-channel color adjusting value of the pixel point according to the maximum value and the maximum standard value in the three-channel color information; and adjusting the three-channel color information of the pixel points according to the color adjusting numerical value.
The reflection component image (second decomposed image) is a color image, each pixel point of the reflection component image has R, G, B three-channel color information (pixel values), and R, G, B three-channel color information may be different from each other, and each color information range is 0-255, and correspondingly, the maximum standard value is 255. Illustratively, the color information of R, G, B three channels of a pixel point in the reflected component image is 200, 150, and 210, respectively, where the maximum value of the color information of the three channels is the color information 210 of the B channel, and a color adjustment value can be determined according to the color information of the B channel and the maximum standard value, for example, the color adjustment value can be a difference value between the maximum standard value and the maximum value of the color information of the three channels, that is, 45, the color information of the three channels is adjusted based on the color adjustment value, that is, the color adjustment value is added on the basis of the color information of the three channels, and illustratively, the adjusted color information of the three channels 245, 195, and 255 is obtained by adding the color adjustment value to the color information of the R, G, B three channels, respectively. And executing the above mode on each pixel point in the reflection component image to obtain the adjusted reflection component image. In this embodiment, the color adjustment value is determined based on the maximum value and the maximum standard value of the color information in the three channels, and the color adjustment is performed on the color information in the three channels according to the color adjustment value, so that the color distortion problem is avoided in the color saturation adjustment process.
It should be noted that, in this embodiment, steps 302 to 304 and step 305 may be performed sequentially, may be performed synchronously, or may be performed first in step 305 and then in steps 302 to 304, which is not limited herein.
According to the image processing method provided by the embodiment of the application, the shadow component image and the reflection component image of the image to be processed are obtained through essential decomposition, the brightness of the shadow component image is adjusted, the color saturation of the reflection component image is adjusted, the pertinence and the efficiency of the brightness adjustment and the color saturation adjustment are improved, the processing processes are not affected mutually, and the image processing quality and the processing effect are improved.
Fig. 4 is a schematic flow chart of another image processing method provided in an embodiment of the present application, where the present embodiment is an alternative to the foregoing embodiment, and accordingly, as shown in fig. 4, the method of the present embodiment includes the following steps:
And step 402, performing brightness adjustment on the texture image to generate a first adjusted image.
And 403, performing image sharpening on the structural image to generate a third adjustment image.
And 404, carrying out image fusion on the first adjusting image and the third adjusting image to generate a first processing image.
In this embodiment, the image to be processed may be decomposed into a texture image and a structural image through morphological component analysis, where the texture information carries luminance information of the image to be processed, and the structural image includes a significant structure in the image to be processed. The brightness adjustment of the texture image can be convenient for the brightness value of the texture image, the brightness distribution of the texture image is generated, the brightness gain of each pixel point is determined based on the standard brightness distribution, and the brightness adjustment of each pixel point of the texture image is performed according to the brightness gain so as to improve the brightness of the texture image.
In this embodiment, the image sharpening process on the structural image may be to respectively obtain preset regions of the structural image with each pixel point as a central pixel point; respectively acquiring intensity information of each pixel point in multiple directions according to a preset region, taking the pixel point of which the original data corresponding to the data with the maximum absolute value in the intensity information in the multiple directions is a positive value as a white edge, and taking the original data corresponding to the data with the maximum absolute value as the sharpening intensity of the white edge; and taking the pixel point of which the original data corresponding to the data with the maximum absolute value in the intensity information in the multiple directions is a negative value as a black edge, taking the original data corresponding to the data with the maximum absolute value as the sharpening intensity of the black edge, and respectively sharpening the black edge and the white edge according to the sharpening intensities corresponding to the black edge and the white edge. Wherein, a plurality of directions include horizontal direction, vertical direction, 45 orientation and 135 orientations, and is corresponding, according to predetermine regional intensity information in a plurality of directions of obtaining respectively each pixel point includes: and respectively acquiring a plurality of pixel points which are symmetrically adjacent in the horizontal direction, the vertical direction, the 45-degree direction and the 135-degree direction by taking the central pixel point as a reference in a preset area, and respectively taking the sum of the difference values of the central pixel point and the plurality of pixel points which are symmetrically adjacent in each direction as the strength information in the corresponding direction. The sharpening process for the black edge and the white edge respectively according to the sharpening strengths corresponding to the black edge and the white edge respectively comprises the following steps: acquiring a sharpening degree parameter of the black edge and a sharpening degree parameter of the white edge; multiplying the sharpening degree parameter of the black edge by the sharpening intensity corresponding to the black edge, and respectively adding the multiplied sharpening degree parameter to each original pixel point of the black edge as a sharpened black edge; and multiplying the sharpening degree parameter of the white edge by the sharpening strength corresponding to the white edge, and respectively adding the parameter to each original pixel point of the white edge as the sharpened white edge. The sharpening degree parameter of the white edge and the sharpening degree parameter of the black edge are both greater than zero, illustratively, the sharpening degree parameter of the black edge is 0.5, and the sharpening degree parameter of the white edge is 0.3.
In this embodiment, after the texture image with the adjusted brightness and the structure image with the sharpening processing are subjected to image fusion, the obtained first processing image not only improves the brightness of the image, but also enhances the definition of the image and improves the quality of the image on the basis of mutual noninterference.
The image processing method provided in the embodiment of the application treats the processed image in a morphological component analysis mode
Fig. 5 is a schematic flow chart of another image processing provided in an embodiment of the present application, where the present embodiment is an alternative to the foregoing embodiment, and accordingly, as shown in fig. 5, the method of the present embodiment includes the following steps:
And 503, performing saturation enhancement processing on the reflection component image to generate a second adjustment image.
And step 504, carrying out image fusion on the first adjusting image and the second adjusting image to generate a first processing image.
And 505, performing morphological component analysis on the first processed image to obtain a texture image and a structural image of the first processed image.
And 507, carrying out image fusion on the texture image and the third adjustment image to generate a second processing image.
In the implementation, brightness adjustment and color saturation adjustment are respectively performed on a shadow component image and a reflection component image obtained by intrinsic decomposition, the brightness and the color saturation of the image to be processed are improved by a first processing image obtained by fusing the adjusted shadow component image and the reflection component image, secondary decomposition is performed on the first processing image to obtain a texture image and a structural image of the first processing image, the structure is sharpened, the outline of the image to be processed is compensated, the edge and gray level jump of the image to be processed is enhanced, and the definition of the image to be processed is improved. In the embodiment, the image to be processed is subjected to image decomposition twice, and the brightness value, the color value and the image structure of the image to be processed are respectively subjected to targeted processing, so that the influence of any processing process on other characteristic parameters is avoided, and the method is strong in pertinence and high in processing efficiency.
It should be noted that, in other embodiments, morphological component analysis may also be performed on the image to be processed to obtain a texture image and a structural image of the image to be processed, brightness adjustment is performed on the texture image, sharpening processing is performed on the structural image, image fusion is performed on the processed texture image and the structural image to generate a first processed image, essential decomposition is performed on the first processed image to obtain a shadow component image and a reflection component image of the first processed image, color saturation adjustment is performed on the reflection component image, and image fusion is performed on the adjusted reflection component image and the shadow component image to generate a second processed image.
Fig. 6 is a block diagram of an image processing apparatus, which may be implemented by software and/or hardware, and is generally integrated in an electronic device, and may process an image by executing an image processing method of the electronic device according to an embodiment of the present disclosure. As shown in fig. 6, the apparatus includes: an image decomposition module 601, a brightness adjustment module 602, and an image fusion module 603.
The image decomposition module 601 is configured to obtain an image to be processed, and perform image decomposition on the image to be processed to obtain a second decomposed image and a first decomposed image carrying image brightness information;
a brightness adjusting module 602, configured to perform brightness adjustment on the first decomposed image to generate a first adjusted image;
an image fusion module 603, configured to perform image fusion on the first adjustment image and the second decomposition image to generate a first processed image.
The image processing device provided in the embodiment of the application performs brightness adjustment on the first decomposed image in a targeted manner by decomposing the first decomposed image carrying image brightness information from the processed image, improves the image brightness without influencing other characteristic parameters of the image, reduces the data processing amount, and improves the image processing efficiency and the image processing effect.
On the basis of the above embodiment, the image decomposition is an essential decomposition, and accordingly, the first decomposed image is a shadow component image, and the second decomposed image is a reflection component image.
On the basis of the above embodiment, the brightness adjusting module 602 includes:
a brightness distribution determining unit that obtains a brightness distribution of the shadow component image by shading;
a gain determination unit configured to determine a gain value of each luminance value according to a gain rule, wherein the gain rule is determined according to a luminance distribution of the shadow component image;
and the brightness processing unit is used for processing each brightness value according to the gain value.
On the basis of the above embodiment, the brightness adjusting module 602 further includes:
the brightness judging unit is used for determining whether each processed brightness value is larger than the maximum value of the brightness range;
and the brightness value adjusting unit is used for determining the brightness value larger than the maximum brightness range value as the maximum brightness range value if each processed brightness value is larger than the maximum brightness range value.
On the basis of the above embodiment, the method further includes:
the saturation processing module is used for performing saturation enhancement processing on the reflection component image to generate a second adjustment image before performing image fusion on the first adjustment image and the second decomposition image;
accordingly, the image fusion module 603 is configured to:
and carrying out image fusion on the first adjusting image and the second adjusting image.
On the basis of the above embodiment, the saturation processing module is configured to:
acquiring three-channel color information of any pixel point in the second decomposition image;
for any pixel point, determining a three-channel color adjusting value of the pixel point according to the maximum value and the maximum standard value in the three-channel color information;
and adjusting the three-channel color information of the pixel points according to the color adjusting numerical value.
On the basis of the above embodiment, the image is decomposed into morphological component analysis, and accordingly, the first decomposed image is a texture image and the second decomposed image is a structural image.
On the basis of the above embodiment, the method further includes:
a sharpening processing module, configured to perform image sharpening processing on the structural image to generate a third adjustment image before performing image fusion on the first adjustment image and the second decomposition image;
accordingly, the image fusion module 603 is configured to:
and carrying out image fusion on the first adjusting image and the third adjusting image.
Embodiments of the present application also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a method of image processing, the method comprising:
acquiring an image to be processed, and performing image decomposition on the image to be processed to obtain a second decomposed image and a first decomposed image carrying image brightness information;
adjusting the brightness of the first decomposition image to generate a first adjustment image;
and carrying out image fusion on the first adjustment image and the second decomposition image to generate a first processing image.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDRRAM, SRAM, EDORAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system connected to the first computer system through a network (such as the internet). The second computer system may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided in the embodiments of the present application contains computer-executable instructions, and the computer-executable instructions are not limited to the image processing operations described above, and may also perform related operations in the image processing method provided in any embodiment of the present application.
The embodiment of the application provides electronic equipment, and the image processing device provided by the embodiment of the application can be integrated in the electronic equipment. Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device 700 may include: the image processing system comprises a memory 701, a processor 702 and a computer program stored on the memory 701 and executable by the processor 702, wherein the processor 702 implements the image processing method according to the embodiment of the present application when executing the computer program.
According to the electronic equipment provided by the embodiment of the application, the first decomposition image carrying the image brightness information is decomposed from the processed image, brightness adjustment is performed on the first decomposition image in a targeted manner, under the condition that other characteristic parameters of the image are not influenced, the image brightness is improved, the data processing amount is reduced, and the image processing efficiency and the image processing effect are improved.
Fig. 8 is a schematic structural diagram of another electronic device according to an embodiment of the present application. The electronic device may include: a housing (not shown), a memory 801, a Central Processing Unit (CPU) 802 (also called a processor, hereinafter referred to as CPU), a circuit board (not shown), and a power circuit (not shown). The circuit board is arranged in a space enclosed by the shell; the CPU802 and the memory 801 are provided on the circuit board; the power supply circuit is used for supplying power to each circuit or device of the electronic equipment; the memory 801 is used for storing executable program codes; the CPU802 executes a computer program corresponding to the executable program code stored in the memory 801 by reading the executable program code to realize the steps of:
acquiring an image to be processed, and performing image decomposition on the image to be processed to obtain a second decomposed image and a first decomposed image carrying image brightness information;
adjusting the brightness of the first decomposition image to generate a first adjustment image;
and carrying out image fusion on the first adjustment image and the second decomposition image to generate a first processing image.
The electronic device further includes: peripheral interface 803, RF (Radio Frequency) circuitry 805, audio circuitry 806, speakers 811, power management chip 808, input/output (I/O) subsystem 809, other input/control devices 810, touch screen 812, other input/control devices 810, and external port 804, which communicate over one or more communication buses or signal lines 807.
It should be understood that the illustrated electronic device 800 is merely one example of an electronic device, and that the electronic device 800 may have more or fewer components than shown in the figures, may combine two or more components, or may have a different configuration of components. The various components shown in the figures may be implemented in hardware, software, or a combination of hardware and software, including one or more signal processing and/or application specific integrated circuits.
The following describes in detail the electronic device for image processing operation provided in this embodiment, which is exemplified by a mobile phone.
A memory 801, the memory 801 being accessible by the CPU802, the peripheral interface 803, and the like, the memory 801 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic disk storage devices, flash memory devices, or other volatile solid state storage devices.
A peripheral interface 803, said peripheral interface 803 allowing input and output peripherals of the device to be connected to the CPU802 and the memory 801.
I/O subsystem 809, which I/O subsystem 809 may connect input and output peripherals on the device, such as touch screen 812 and other input/control devices 810, to peripheral interface 803. The I/O subsystem 809 may include a display controller 8091 and one or more input controllers 8092 for controlling other input/control devices 810. Where one or more input controllers 8092 receive electrical signals from or transmit electrical signals to other input/control devices 810, other input/control devices 810 may include physical buttons (push buttons, rocker buttons, etc.), dials, slide switches, joysticks, click wheels. It is worth noting that the input controller 8092 may be connected to any of the following: a keyboard, an infrared port, a USB interface, and a pointing device such as a mouse.
A touch screen 812, which touch screen 812 is an input interface and an output interface between the consumer electronic device and the user, displays visual output to the user, which may include graphics, text, icons, video, and the like.
The display controller 8091 in the I/O subsystem 809 receives electrical signals from the touch screen 812 or sends electrical signals to the touch screen 812. The touch screen 812 detects a contact on the touch screen, and the display controller 8091 converts the detected contact into an interaction with a user interface object displayed on the touch screen 812, that is, implements a human-computer interaction, and the user interface object displayed on the touch screen 812 may be an icon for running a game, an icon networked to a corresponding network, or the like. It is worth mentioning that the device may also comprise a light mouse, which is a touch sensitive surface that does not show visual output, or an extension of the touch sensitive surface formed by the touch screen.
The RF circuit 805 is mainly used to establish communication between the mobile phone and the wireless network (i.e., the network side), and implement data reception and transmission between the mobile phone and the wireless network. Such as sending and receiving short messages, e-mails, etc. In particular, the RF circuitry 805 receives and transmits RF signals, also referred to as electromagnetic signals, which the RF circuitry 805 converts to or from electrical signals, and communicates with communication networks and other devices over. RF circuitry 805 may include known circuitry for performing these functions including, but not limited to, an antenna system, an RF transceiver, one or more amplifiers, a tuner, one or more oscillators, a digital signal processor, a CODEC (CODEC) chipset, a Subscriber Identity Module (SIM), and so forth.
The audio circuit 806 is mainly used to receive audio data from the peripheral interface 803, convert the audio data into an electric signal, and transmit the electric signal to the speaker 811.
The speaker 811 is used to convert the voice signal received by the handset from the wireless network through the RF circuit 805 into sound and play the sound to the user.
And the power management chip 808 is used for supplying power and managing power to the hardware connected with the CPU802, the I/O subsystem and the peripheral interface.
The image processing apparatus, the storage medium, and the electronic device provided in the above embodiments may execute the image processing method provided in any embodiment of the present application, and have corresponding functional modules and advantageous effects for executing the method. For details of the image processing method provided in any of the embodiments of the present application, reference may be made to the following description.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (7)
1. An image processing method, comprising:
acquiring an image to be processed, and performing essential decomposition on the image to be processed to obtain a reflection component image and a shadow component image carrying image brightness information;
adjusting the brightness of the shadow component image to generate a first adjusted image;
performing saturation enhancement processing on the reflection component image to generate a second adjustment image;
carrying out image fusion on the first adjusting image and the second adjusting image to generate a first processing image;
performing morphological component analysis on the first processed image to obtain a texture image and a structural image of the first processed image;
carrying out image sharpening on the structural image to generate a third adjusting image;
and carrying out image fusion on the texture image and the third adjusting image to generate a second processing image.
2. The method of claim 1, wherein performing a brightness adjustment on the shadow component image to generate a first adjusted image comprises:
acquiring the brightness distribution of the shadow component image;
determining a gain value of each brightness value according to a gain rule, wherein the gain rule is determined according to the brightness distribution of the shadow component image;
and processing each brightness value according to the gain value.
3. The method of claim 2, further comprising:
determining whether each processed brightness value is larger than the maximum value of the brightness range;
and if so, adjusting the brightness value larger than the maximum value of the brightness range to be the maximum value of the brightness range.
4. The method of claim 1, wherein performing saturation enhancement processing on the reflected component image to generate a second adjusted image comprises:
acquiring color information of three channels of any pixel point in the reflection component image;
for any pixel point, determining a three-channel color adjusting value of the pixel point according to the maximum value and the maximum standard value in the three-channel color information;
and adjusting the three-channel color information of the pixel points according to the color adjusting numerical value.
5. An image processing apparatus characterized by comprising:
the image decomposition module is used for acquiring an image to be processed and carrying out essential decomposition on the image to be processed to obtain a reflection component image and a shadow component image carrying image brightness information;
the brightness adjusting module is used for adjusting the brightness of the shadow component image to generate a first adjusting image;
the saturation processing module is used for performing saturation enhancement processing on the reflection component image to generate a second adjustment image;
the image fusion module is used for carrying out image fusion on the first adjusting image and the second adjusting image to generate a first processing image;
the image decomposition module is further used for performing morphological component analysis on the first processed image to obtain a texture image and a structural image of the first processed image;
the sharpening processing module is used for carrying out image sharpening processing on the structural image to generate a third adjusting image;
the image fusion module is further configured to perform image fusion on the texture image and the third adjustment image to generate a second processed image.
6. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the image processing method according to any one of claims 1 to 4.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the image processing method according to any one of claims 1 to 4 when executing the computer program.
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| CN112308803B (en) * | 2020-11-25 | 2021-10-01 | 哈尔滨工业大学 | Self-supervision low-illumination image enhancement and denoising method based on deep learning |
| CN113781370A (en) * | 2021-08-19 | 2021-12-10 | 北京旷视科技有限公司 | Image enhancement method and device and electronic equipment |
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| CN101639537B (en) * | 2009-09-04 | 2011-08-24 | 西安电子科技大学 | SAR image noise suppression method based on direction wave domain mixture Gaussian model |
| CN103218778B (en) * | 2013-03-22 | 2015-12-02 | 华为技术有限公司 | The disposal route of a kind of image and video and device |
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| CN104580925A (en) * | 2014-12-31 | 2015-04-29 | 安科智慧城市技术（中国）有限公司 | Image brightness controlling method, device and camera |
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