CN114782266A - Digital image signal space domain denoising method, device, equipment and medium - Google Patents
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Abstract
The invention provides a digital image signal space domain denoising method, a device, equipment and a medium, which comprises the steps of obtaining an original image to be denoised, and performing column scanning on the original image to be denoised to generate a plurality of original pixel block columns; copying original pixel block columns to generate a plurality of first original pixel block columns, carrying out color modulization on the first original pixel block columns, and inputting the processed first original pixel block columns into a statistical data queue in columns; copying the original pixel block columns to generate a plurality of second original pixel block columns, inputting the second original pixel block columns into the buffer data queue in columns, and generating central pixel block values of the second original pixel block columns; copying the central pixel block value to generate a value for judgment and processing; carrying out color modularization on the judgment value, counting the number of the numerical values with the same value of the residual judgment value in the statistical data queue, and carrying out ratio processing to generate data frequency; and judging noise points by using the data frequency to generate a denoised image. In addition, the traditional image signal denoising method does not separately identify noise points, so that the denoising operation efficiency is low and the smearing phenomenon is obvious.
Description
Technical Field
The invention relates to the technical field of digital image signal processing, in particular to a method, a device, equipment and a medium for denoising a digital image signal in a spatial domain.
Background
Image noise is generally generated in the processes of image acquisition and transmission, and in the processes, the generation of the noise is inevitable due to factors such as electronic interference, external fluctuation and the like; therefore, the denoising processing of the image plays an important role in the image processing field, and the denoising is not only for acquiring a more accurate and real image, but also for making an important cushion for the subsequent processing of the image, and is an essential key technology in the image preprocessing.
The traditional image signal space domain denoising method comprises a mean filtering algorithm, a median filtering algorithm, a self-adaptive filtering algorithm, a maximum filtering algorithm and the like, which have advantages and disadvantages, but the methods mostly carry out undifferentiated processing on all pixel blocks of an image and do not separately identify and process noise points, so that the denoising operation efficiency is low, and the smearing phenomenon is obvious.
In view of this, the present application is presented.
Disclosure of Invention
The invention discloses a method, a device, equipment and a medium for denoising a digital image signal space domain, which can effectively solve the problems of low denoising operation efficiency and obvious smearing phenomenon caused by the fact that the traditional image signal space domain denoising method carries out undifferentiated processing on all pixel blocks of an image and does not independently carry out recognition processing on noise points.
The invention discloses a digital image signal space domain denoising method, which comprises the following steps:
acquiring an original image to be denoised, and performing column scanning processing on the original image to generate a plurality of original pixel block columns;
copying each original pixel block column to generate a plurality of first original pixel block columns, performing color modularization processing on the first original pixel block columns, and inputting the processed first original pixel block columns into a statistical data queue according to the column sequence, wherein the color modularization processing is to take the residue of a pixel block value and a preset minimum scale unit, and subtract the residue by the pixel block value to obtain an output value;
copying each original pixel block column to generate a plurality of second original pixel block columns, inputting the second original pixel block columns into a buffer data queue in a column sequence, and generating a central pixel block value of the second original pixel block columns;
copying the central pixel block value to generate a judgment value and a processing value;
carrying out color modularization processing on the judgment value, counting the number of numerical values with the same value as the remainder judgment value in the statistical data queue, and carrying out ratio processing on the numerical values and the statistical data queue to generate data frequency;
and judging noise by using the data frequency to generate a denoised image, wherein the data frequency is compared with a preset data frequency threshold, when the data frequency is judged to be not lower than the preset data frequency threshold, a pixel block corresponding to the data frequency is an effective pixel block, and when the data frequency is judged to be lower than the preset data frequency threshold, the pixel block corresponding to the data frequency is a noise pixel block.
Preferably, inputting the processed first original pixel block column into a statistical data queue in a column order specifically comprises:
inputting the processed first original pixel block into the tail end of the statistical data queue according to the sequence of columns;
and popping up and discarding a column of data at the front end of the statistical data queue, wherein the statistical data queue is a data statistical window with a fixed size.
Preferably, the second original pixel block column is input into a buffer data queue in a column sequence, and a central pixel block value of the second original pixel block column is generated, specifically:
inputting the second original pixel block column into the tail end of a buffer data queue according to the sequence of columns;
and popping and discarding a row of data at the front end of the buffer data queue to generate a central pixel block value of the second original pixel block row, wherein the buffer data queue is a data storage window with a fixed size, and the central pixel block value is a brightness value of each of the RGB colors of the central pixel block in the second original pixel block row.
Preferably, the determination value is subjected to color modulization, and the number of values having the same value as the remainder determination value in the statistical data queue is counted, and the statistical data queue is subjected to ratio processing to generate a data frequency, specifically:
performing color modulus processing on the judgment value to generate a surplus judgment value;
comparing the remainder judgment value with the statistical data queue to obtain the number of numerical values in the statistical data queue, wherein the numerical values are the same as the remainder judgment value;
and performing ratio probability calculation on the number and the total number of the numerical values of the statistical data queue to generate data frequency, wherein the data frequency is the ratio of the number to the total number of the numerical values of the statistical data queue.
Preferably, the data frequency is used to determine a noise point, so as to generate a de-noised image, specifically:
performing difference processing on the data frequency and the preset data frequency threshold to generate a noise pixel block and an effective pixel block;
carrying out color average processing on the processing value of the noise pixel block to generate a color average value as an output value;
the processing value of the effective pixel block is not processed and is directly used as an output value;
and combining all the output values to generate a denoised image.
Preferably, the difference processing is performed on the data frequency and the preset data frequency threshold to generate a noise pixel block and an effective pixel block, specifically:
the difference value is made between the data frequency and the preset data frequency threshold value, and a frequency difference value is generated;
judging whether the frequency difference value is larger than zero or not;
if yes, determining the pixel block corresponding to the data frequency as an effective pixel block;
if not, the pixel block corresponding to the data frequency is judged to be a noise pixel block.
Preferably, the processing value of the noise pixel block is color-averaged to generate a color average value as an output value, specifically:
acquiring four pixel block values of the noise pixel block which are adjacent from top to bottom, left to right in the buffer data queue;
and calculating the average value of four pixel block values adjacent to each other up, down, left and right to generate a color average value.
The invention discloses a digital image signal space domain denoising device, which comprises:
the device comprises an original pixel block column acquisition unit, a de-noising unit and a de-noising unit, wherein the original pixel block column acquisition unit is used for acquiring an original image to be de-noised, and performing column scanning processing on the original image to generate a plurality of original pixel block columns;
a statistical data queue obtaining unit, configured to copy each original pixel block column, generate a plurality of first original pixel block columns, perform color modulization on the first original pixel block columns, and input the processed first original pixel block columns into a statistical data queue in a column order, where the color modulization is to perform remainder on a pixel block value and a preset minimum scale unit, and subtract a remainder from the pixel block value to obtain an output value;
a buffer data queue obtaining unit, configured to copy each original pixel block column, generate a plurality of second original pixel block columns, input the second original pixel block columns into the buffer data queue in a column sequence, and generate a central pixel block value of the second original pixel block columns;
a central pixel block value copying unit for copying the central pixel block value and generating a value for judgment and a value for processing;
the frequency calculation unit is used for carrying out color modulus processing on the judgment value, counting the number of numerical values which have the same value with the surplus judgment value in the statistical data queue, carrying out ratio processing on the numerical values and the statistical data queue, and generating data frequency;
and the de-noised image generating unit is used for judging noise by using the data frequency and generating a de-noised image, wherein the data frequency is compared with a preset data frequency threshold, when the data frequency is judged to be not lower than the preset data frequency threshold, the pixel block corresponding to the data frequency is an effective pixel block, and when the data frequency is judged to be lower than the preset data frequency threshold, the pixel block corresponding to the data frequency is a noise pixel block.
The invention discloses a digital image signal space domain denoising device, which comprises a processor, a memory and a computer program stored in the memory and configured to be executed by the processor, wherein the processor realizes the digital image signal space domain denoising method when executing the computer program.
The invention discloses a readable storage medium, which stores a computer program, wherein the computer program can be executed by a processor of a device on which the storage medium is arranged, so as to realize the digital image signal space domain denoising method.
In summary, the digital image signal space domain denoising method, apparatus, device and medium provided in this embodiment can identify noise points in an image based on a probability statistics principle, and process the noise points individually without changing other pixel blocks; after an original image to be denoised is obtained, the original image is scanned, the original image is divided into a plurality of original pixel block columns and is copied into two parts, one part is directly input into a statistical data queue after being subjected to color modulus processing, the other part is directly input into a buffer data queue, a central pixel block value output by the buffer data queue is copied into two parts, the other part is subjected to color modulus processing and then is subjected to ratio with the statistical data queue, the data frequency is calculated and compared with a preset data frequency threshold, processed noise pixel blocks and effective pixel blocks are respectively output under the condition that the compared data frequency is lower than or not lower than the preset data frequency threshold, and a corresponding denoised image is generated, so that the problem that the traditional image signal space domain denoising method carries out undifferentiated processing on all pixel blocks of the image and does not separately identify noise is solved, the method has the problems of low denoising operation efficiency and obvious smearing phenomenon.
Drawings
Fig. 1 is a schematic flow chart of a digital image signal space domain denoising method provided by an embodiment of the present invention.
Fig. 2 is a schematic diagram of a specific operation flow of the digital image signal space domain denoising method according to the embodiment of the present invention.
Fig. 3 is a schematic diagram of an operation flow of color modulization processing of a digital image signal space domain denoising method provided by an embodiment of the present invention.
Fig. 4 is a schematic overall operation flow diagram of the digital image signal space domain denoising method provided by the embodiment of the invention.
Fig. 5 is a schematic diagram of an operation flow of color averaging in the method for denoising a digital image signal in a spatial domain according to an embodiment of the present invention.
Fig. 6 is a schematic block diagram of a digital image signal space domain denoising apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings of the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without inventive efforts based on the embodiments of the present invention, are within the scope of protection of the present invention.
The following detailed description of specific embodiments of the invention refers to the accompanying drawings.
Referring to fig. 1 to fig. 2, a first embodiment of the present invention provides a method for denoising a digital image signal in a spatial domain, including:
s101, acquiring an original image to be denoised, and performing column scanning processing on the original image to generate a plurality of original pixel block columns;
specifically, in this embodiment, taking an N-dimensional column vector as a unit, scanning an original image by columns as an example: obtaining a plurality of original pixel block rows and obtaining original pixel block values; the N-dimensional column vector is a matrix of N rows and 1 column, the original pixel block column includes N original pixel blocks, the original pixel block includes an effective pixel block and a noise pixel block, the pixel block value refers to a color value of the pixel block, and the color value refers to a luminance value of each of RGB.
S102, copying each original pixel block column, generating a plurality of first original pixel block columns, performing color modularization processing on the first original pixel block columns, and inputting the processed first original pixel block columns into a statistical data queue in a column sequence, wherein the color modularization processing is to take the residue of a pixel block value and a preset minimum scale unit and subtract the residue by the pixel block value to obtain an output value;
referring to fig. 3, specifically, in this embodiment, the step of inputting the processed first original pixel block column into the statistical data queue in a column order includes:
inputting the processed first original pixel block into the tail end of the statistical data queue according to the sequence of columns;
and popping up and discarding a column of data at the front end of the statistical data queue, wherein the statistical data queue is a data statistical window with a fixed size.
Specifically, in this embodiment, taking an N-dimensional column vector as a unit, scanning an RGB image with salt-and-pepper noise by columns as an example of an original image: the original image is composed of a plurality of pixel blocks, and each pixel block comprises respective brightness values of three colors of RGB; copying the values of a plurality of original pixel block columns obtained by scanning, and performing color modular processing on one original pixel block column by one column, wherein the color modular processing refers to the process of taking the pixel block value and a preset minimum scale unit and subtracting the remainder from the pixel block value to obtain an output value, and the preset minimum scale unit is the resolution of a color numerical value. The processed pixel block column is arranged into the tail end of a statistical data queue, and the size of the statistical data queue is equal toN×NThe data statistical window is used for calculating the frequency of the central pixel block value of the window in the statistical data queue, the tail end is the entering, the head end is popped up, and the popped-up column is discarded according to the first-in first-out. The end of the window is popped in at the beginning and follows a first-in first-out, to keep the window size constant, the popped pixel block column is discarded and no output of the statistical data queue is used only to calculate the frequency.
S103, copying each original pixel block column to generate a plurality of second original pixel block columns, inputting the second original pixel block columns into a buffer data queue according to the column sequence, and generating a central pixel block value of the second original pixel block columns;
specifically, in this embodiment, the step of inputting the second original pixel block column into the buffer data queue in a column order to generate a central pixel block value of the second original pixel block column specifically includes:
inputting the second original pixel block column into the tail end of a buffer data queue according to the sequence of columns;
and popping and discarding a row of data at the front end of the buffer data queue to generate a central pixel block value of the second original pixel block row, wherein the buffer data queue is a data storage window with a fixed size, and the central pixel block value is a brightness value of each of the RGB colors of the central pixel block in the second original pixel block row.
In particular toIn the embodiment, taking an N-dimensional column vector as a unit, scanning an original image by columns is taken as an example: copying the values of a plurality of original pixel block columns obtained by scanning, directly entering one original pixel block column into the tail end of a buffer data queue according to the column, wherein the size of the buffer data queue is equal to
(i.e., the quotient of N divided by 2 rounded up and multiplied by N) for temporarily storing data, the output of which is the center tile value of the pop-up tile column, i.e., the first
The value of the tile number. The window ends for entry and the head pops up and follows a first-in-first-out, keeping the window size unchanged.
S104, copying the central pixel block value to generate a judgment value and a processing value;
specifically, in this embodiment, the central pixel block value is copied, one is a judgment value, and the other is a processing value, and the judgment value is color-modularized, where the judgment value refers to a pixel block value used for calculating data frequency and performing judgment in the following step, the processing value refers to a pixel block value subjected to color averaging or unchanged after the judgment is completed, the color-modularized processing refers to obtaining an output value by subtracting a remainder from a preset minimum scale unit, and the preset minimum scale unit is a resolution of a color value.
S105, performing color modulization processing on the judgment value, counting the number of numerical values which are in the same value as the remainder judgment value in the statistical data queue, performing ratio processing on the numerical values and the statistical data queue, and generating data frequency;
specifically, in this embodiment, the color modulus processing is performed on the value for judgment, the number of the numerical values in the statistical data queue having the same value as the remainder value for judgment is counted, the numerical values and the statistical data queue are subjected to ratio processing, and the data frequency is generated, specifically:
performing color modulus processing on the judgment value to generate a surplus judgment value;
comparing the remainder judgment value with the statistical data queue to obtain the number of numerical values in the statistical data queue, which have the same value as the remainder judgment value;
and carrying out ratio probability calculation on the number and the total number of the numerical values of the statistical data queue to generate data frequency, wherein the data frequency is the ratio of the number to the total number of the numerical values of the statistical data queue.
Specifically, in this embodiment, the frequency of the color-modulized determination value in the statistical data queue is calculated by using the color-modulized determination value as the central pixel block value of the statistical data queue. Firstly, obtaining a value for judgment after modulization, then obtaining the number of values which have the same value as the value in a statistical data queue, and calculating the frequency of the values according to the total number of data in the statistical data queue; specifically, the data frequency is obtained by comparing the number of values having the same value as the judgment value in the statistical data queue with the total number of data in the statistical data queue.
And S106, performing noise point judgment by using the data frequency to generate a noise-removed image, wherein the data frequency is compared with a preset data frequency threshold, when the data frequency is judged to be not lower than the preset data frequency threshold, a pixel block corresponding to the data frequency is an effective pixel block, and when the data frequency is judged to be lower than the preset data frequency threshold, the pixel block corresponding to the data frequency is a noise point pixel block.
Referring to fig. 4, in this embodiment, specifically, the noise point determination is performed by using the data frequency to generate a denoised image, which specifically includes:
performing difference processing on the data frequency and the preset data frequency threshold to generate a noise pixel block and an effective pixel block;
carrying out color average processing on the processing value of the noise pixel block to generate a color average value as an output value;
the processing value of the effective pixel block is not processed and is directly used as an output value;
and combining all the output values to generate a denoised image.
In this embodiment, performing difference processing on the data frequency and the preset data frequency threshold to generate a noise pixel block and an effective pixel block specifically includes:
the difference value is made between the data frequency and the preset data frequency threshold value, and a frequency difference value is generated;
judging whether the frequency difference value is larger than zero or not;
if yes, judging the pixel block corresponding to the data frequency as an effective pixel block;
if not, the pixel block corresponding to the data frequency is judged to be a noise pixel block.
Referring to fig. 5, in this embodiment, the processing value of the noise pixel block is color-averaged to generate a color average value as an output value, which specifically includes:
acquiring four pixel block values of the noise pixel block which are adjacent from top to bottom, left to right in the buffer data queue;
and calculating the average value of four pixel block values adjacent to each other up, down, left and right to generate a color average value.
In this embodiment, noise point determination is performed on a pixel block according to the data frequency, and color averaging and output are performed on the noise points, and finally a denoised image is synthesized; specifically, the noise point determination refers to comparing with a preset data frequency threshold, if the frequency of the color-modulized value for determination in the statistical data queue is not lower than the data frequency threshold, determining the color-modulized value for determination as an effective pixel block, and outputting and assembling the value for processing into an output image; and if the frequency of the judgment value after the color modulization in the statistical data queue is lower than a data frequency threshold value, judging the judgment value as a noise pixel block, wherein the noise processing value is subjected to color averaging to obtain the color average value of the noise processing value, and the color average value is obtained by assigning the average value of adjacent block values to the noise pixel block. More specifically, the noise point determination means that the calculated data frequency is subjected to difference processing with a preset data frequency threshold, and whether the pixel block is a noise point pixel block is determined according to a difference processing result; if the difference processing result is less than zero, judging that the point is a noise pixel block, carrying out color average processing on the processing value of the noise pixel block, and then outputting the noise pixel block; if the difference processing result is larger than zero, the point is judged to be an effective pixel block, and the processing value is directly output without processing.
And finally, sequentially outputting a plurality of pixel blocks by each original pixel block through the process to form a denoised image. The user can adjust the denoising effect of the digital image signal space domain denoising method by setting different minimum scale units, counting the size of a data queue and presetting a data frequency threshold. In addition, the digital image signal space domain denoising method essentially utilizes the probability that the noise point pixel block is lower than the probability of the effective pixel block, and the noise point probability is generally lower than the probability of the effective pixel block due to the peculiarity of the salt and pepper noise, so the method can effectively denoise the salt and pepper noise; and for sparsely distributed interference noise points generated by fluctuation in the image transmission process, the method can also be used for effectively filtering.
In summary, the digital image signal space domain denoising method scans an original image by rows by taking an N-dimensional row vector as a unit to obtain a plurality of original pixel block rows and obtain original pixel block values; copying the values of a plurality of original pixel block columns obtained by scanning, directly entering one part of original pixel block columns into the tail end of a buffer data queue according to the columns, copying the pixel block values output by the original pixel block columns, wherein one part of original pixel block columns is a value for judgment, the other part of original pixel block columns is a value for processing, and the value for judgment is subjected to color modulus processing; performing color modulus processing on the other original pixel block row one by one according to rows, then entering the processed pixel block row into the tail end of a statistical data queue according to rows, and calculating the frequency of the color modulus judging value in the statistical data queue by using the color modulus judging value as the central pixel block value of the statistical data queue; and according to the calculation result, carrying out noise point judgment on the pixel block, carrying out color average on the noise points and outputting, and finally synthesizing a de-noised image. The digital image signal space domain denoising method is used for independently identifying and processing the noise points, so that the operation efficiency is improved, and the smearing phenomenon is greatly improved.
The digital image signal space domain denoising method is simple in operation steps, few in operation times, few in resource occupation and high in operation efficiency, so that the signal image can be efficiently processed; the digital image signal space domain denoising method can effectively identify noise points in the digital image signal and filter the noise points, so that the influence on the subsequent processing process of the image is avoided, and the reliability is high; the digital image signal space domain denoising method can adjust the denoising effect of the invention by setting different minimum scale units, counting the size of the data queue and presetting the data frequency threshold, and is flexible and simple to operate.
Referring to fig. 6, a second embodiment of the present invention provides a digital image signal space domain denoising apparatus, including:
an original pixel block column acquiring unit 201, configured to acquire an original image to be denoised, perform column scanning processing on the original image, and generate a plurality of original pixel block columns;
a statistical data queue obtaining unit 202, configured to copy each original pixel block column, generate a plurality of first original pixel block columns, perform color modulization on the first original pixel block columns, and input the processed first original pixel block columns into a statistical data queue according to a column sequence, where the color modulization is to perform remainder on a pixel block value and a preset minimum scale unit, and subtract a remainder from the pixel block value to obtain an output value;
a buffer data queue obtaining unit 203, configured to copy each original pixel block column, generate a plurality of second original pixel block columns, input the second original pixel block columns into the buffer data queue in a column sequence, and generate a central pixel block value of the second original pixel block column;
a central pixel block value copying unit 204 configured to copy the central pixel block value and generate a value for determination and a value for processing;
a frequency calculation unit 205, configured to perform color modulus processing on the value for determination, count the number of values in the statistical data queue that have the same value as the remainder value for determination, perform ratio processing on the value and the statistical data queue, and generate a data frequency;
a denoised image generating unit 206, configured to perform noise point determination by using the data frequency, and generate a denoised image, where the data frequency is compared with a preset data frequency threshold, a pixel block corresponding to the data frequency is an effective pixel block when the data frequency is determined to be not lower than the preset data frequency threshold, and the pixel block corresponding to the data frequency is a noise point pixel block when the data frequency is determined to be lower than the preset data frequency threshold.
A third embodiment of the present invention provides a digital image signal space domain denoising apparatus, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements the digital image signal space domain denoising method as described in any one of the above.
A fourth embodiment of the present invention provides a readable storage medium, which stores a computer program, where the computer program can be executed by a processor of a device on which the storage medium is located, so as to implement the digital image signal space domain denoising method as described in any one of the above.
Illustratively, the computer programs described in the third and fourth embodiments of the present invention may be partitioned into one or more modules, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules can be a series of instruction segments of a computer program capable of implementing specific functions, and the instruction segments are used for describing the execution process of the computer program in the device for denoising the digital image signal in a space domain. For example, the device described in the second embodiment of the present invention.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. The general processor can be a microprocessor or the processor can be any conventional processor, etc., the processor is a control center of the digital image signal space domain denoising method, and various interfaces and lines are used for connecting all parts of the digital image signal space domain denoising method.
The memory can be used for storing the computer program and/or the module, and the processor realizes various functions of a digital image signal space domain denoising method by operating or executing the computer program and/or the module stored in the memory and calling data stored in the memory. The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required by at least one function (such as a sound playing function, a text conversion function, etc.), and the like; the storage data area may store data (such as audio data, text message data, etc.) created according to the use of the cellular phone, etc. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
Wherein, the implemented module can be stored in a computer readable storage medium if it is implemented in the form of software functional unit and sold or used as an independent product. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments described above may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, and software distribution medium, etc. It should be noted that the computer-readable medium may contain suitable additions or subtractions depending on the requirements of legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer-readable media may not include electrical carrier signals or telecommunication signals in accordance with legislation and patent practice.
It should be noted that the above-described device embodiments are merely illustrative, where the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the embodiment of the apparatus provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, and may be specifically implemented as one or more communication buses or signal lines. One of ordinary skill in the art can understand and implement without inventive effort.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention.
Claims (10)
1. A method for denoising a digital image signal in a spatial domain is characterized by comprising the following steps:
acquiring an original image to be denoised, and performing column scanning processing on the original image to generate a plurality of original pixel block columns;
copying each original pixel block column to generate a plurality of first original pixel block columns, performing color modularization processing on the first original pixel block columns, and inputting the processed first original pixel block columns into a statistical data queue according to the column sequence, wherein the color modularization processing is to take the residue of a pixel block value and a preset minimum scale unit, and subtract the residue by the pixel block value to obtain an output value;
copying each original pixel block column to generate a plurality of second original pixel block columns, inputting the second original pixel block columns into a buffer data queue in a column sequence, and generating a central pixel block value of the second original pixel block columns;
copying the central pixel block value to generate a judgment value and a processing value;
carrying out color modularization processing on the judgment value, counting the number of numerical values with the same value as the remainder judgment value in the statistical data queue, and carrying out ratio processing on the numerical values and the statistical data queue to generate data frequency;
and judging noise by using the data frequency to generate a denoised image, wherein the data frequency is compared with a preset data frequency threshold, when the data frequency is judged to be not lower than the preset data frequency threshold, a pixel block corresponding to the data frequency is an effective pixel block, and when the data frequency is judged to be lower than the preset data frequency threshold, the pixel block corresponding to the data frequency is a noise pixel block.
2. The method for denoising in the spatial domain of a digital image signal according to claim 1, wherein the step of inputting the processed first original pixel block column into a statistical data queue in the order of columns is specifically:
inputting the processed first original pixel block into the tail end of the statistical data queue according to the sequence of columns;
and popping up and discarding a column of data at the front end of the statistical data queue, wherein the statistical data queue is a data statistical window with a fixed size.
3. The method for denoising a digital image signal according to claim 1, wherein the second original pixel block column is input into a buffer data queue in a column order to generate a central pixel block value of the second original pixel block column, specifically:
inputting the second original pixel block column into the tail end of a buffer data queue according to the sequence of columns;
and popping and discarding a row of data at the front end of the buffer data queue to generate a central pixel block value of the second original pixel block row, wherein the buffer data queue is a data storage window with a fixed size, and the central pixel block value is the brightness value of each RGB color of the central pixel block in the second original pixel block row.
4. The method for denoising the digital image signal in the spatial domain according to claim 1, wherein the judging value is color-modulized, and the number of the numerical values having the same value as the remainder judging value in the statistical data queue is counted, and the numerical values are subjected to ratio processing with the statistical data queue to generate a data frequency, specifically:
performing color modulus processing on the judgment value to generate a surplus judgment value;
comparing the remainder judgment value with the statistical data queue to obtain the number of numerical values in the statistical data queue, which have the same value as the remainder judgment value;
and performing ratio probability calculation on the number and the total number of the numerical values of the statistical data queue to generate data frequency, wherein the data frequency is the ratio of the number to the total number of the numerical values of the statistical data queue.
5. The method for denoising a digital image signal in a spatial domain according to claim 1, wherein the data frequency is used for noise point determination to generate a denoised image, specifically:
performing difference processing on the data frequency and the preset data frequency threshold to generate a noise pixel block and an effective pixel block;
carrying out color average processing on the processing value of the noise pixel block to generate a color average value serving as an output value;
the processing value of the effective pixel block is not processed and is directly used as an output value;
and combining all the output values to generate a denoised image.
6. The method for denoising a digital image signal in a spatial domain according to claim 5, wherein the difference processing is performed on the data frequency and the preset data frequency threshold to generate a noise pixel block and an effective pixel block, specifically:
the data frequency is different from the preset data frequency threshold value to generate a frequency difference value;
judging whether the frequency difference value is larger than zero or not;
if yes, judging the pixel block corresponding to the data frequency as an effective pixel block;
if not, the pixel block corresponding to the data frequency is judged to be a noise pixel block.
7. The method for denoising a digital image signal according to claim 5, wherein the values for processing the noise pixel blocks are color-averaged to generate a color average value as an output value, specifically:
acquiring four pixel block values of the noise pixel block which are adjacent from top to bottom, left to right in the buffer data queue;
and calculating the average value of four pixel block values adjacent to each other up, down, left and right to generate a color average value.
8. A digital image signal space domain denoising device is characterized by comprising:
an original pixel block column acquisition unit, configured to acquire an original image to be denoised, and perform column scanning on the original image to generate a plurality of original pixel block columns;
a statistical data queue obtaining unit, configured to copy each original pixel block column, generate a plurality of first original pixel block columns, perform color modular processing on the first original pixel block columns, and input the processed first original pixel block columns into a statistical data queue in a column sequence, where the color modular processing is to add a remainder to a pixel block value and a preset minimum scale unit, and subtract the remainder from the pixel block value to obtain an output value;
a buffer data queue obtaining unit, configured to copy each original pixel block column, generate a plurality of second original pixel block columns, input the second original pixel block columns into the buffer data queue in a column sequence, and generate a central pixel block value of the second original pixel block columns;
a central pixel block value copying unit for copying the central pixel block value and generating a value for judgment and a value for processing;
the frequency calculation unit is used for carrying out color modulus processing on the judgment value, counting the number of numerical values which have the same value with the surplus judgment value in the statistical data queue, carrying out ratio processing on the numerical values and the statistical data queue, and generating data frequency;
and the de-noising image generating unit is used for judging noise by using the data frequency to generate a de-noising image, wherein the data frequency is compared with a preset data frequency threshold, when the data frequency is judged to be not lower than the preset data frequency threshold, a pixel block corresponding to the data frequency is an effective pixel block, and when the data frequency is judged to be lower than the preset data frequency threshold, the pixel block corresponding to the data frequency is a noise pixel block.
9. A digital image signal spatial domain denoising apparatus, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the digital image signal spatial domain denoising method according to any one of claims 1 to 7 when executing the computer program.
10. A readable storage medium, characterized in that a computer program is stored, which is executable by a processor of a device on which the storage medium is located, so as to implement the method for denoising in the spatial domain of a digital image signal according to any one of claims 1 to 7.
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