JP4809190B2 - Signal processing apparatus and change information generation method - Google Patents

Description

  The present invention relates to a signal processing apparatus and a change information generation method.

  Conventionally, in the process of signal measurement, observation, and recording, it is often impossible to accurately observe and / or record a true input signal, which is an ideal signal, due to the response characteristics of a signal processing system or the influence of noise. . For this reason, when an input signal is to be obtained from an observed and / or recorded output signal, there is a technique such as using the response characteristics of the signal processing system to reverse-convert the output signal into an input signal. It is used.

  As a signal restoration algorithm, a Wiener filter, a general inverse filter, an iterative method and the like have been known for a long time. These are algorithms that express the degradation due to the response characteristics of the signal processing system as a transfer function, and restore the input signal without degradation using the transfer function from the output signal, which is an observation signal obtained through the signal processing system (non-patent) Reference 1).

  When the signal to be handled is an image signal, restoration of a blurred image is the easiest example. For example, an input image that is an ideal signal is an image without blurring. The blur at the time of photographing becomes a response characteristic of the signal processing system that deteriorates the image. Then, a blurred image that is a deterioration (change) signal is obtained as an output signal. When the blur information at the time of shooting and the above-described signal restoration algorithm are used, the blurred image is restored to an image without blur (Non-Patent Document 2). For example, Patent Document 1 proposes a technique for restoring a blurred image by obtaining a transfer function after detecting blur information.

Supervised by Shigeo Minami, edited by Atsushi Kawada, "Introduction to data processing for scientific measurement", CQ Publisher, published on January 10, 2002 Supervised by Mikio Takagi and Yoshihisa Shimoda, “New Image Analysis Handbook”, published by the University of Tokyo Press, September 9, 2004 Japanese Patent Laid-Open No. 11-24122

  When attempting to perform signal restoration, it is important that the relationship between the output signal and the response characteristics of the signal processing system is accurately acquired. Non-Patent Documents 1 and 2 describe a technique for restoring a deteriorated signal or a deteriorated image to an ideal signal without deterioration on the assumption that the deterioration function that is the response characteristic of the signal processing system is accurate.

  However, it is difficult to accurately obtain the relationship between the output signal and the response characteristics of the signal processing system, and errors or noise are always included. Therefore, even if the camera shake image restoration technique described in Patent Document 1 is adopted, if the detection accuracy of the shake information is low, or if there is noise in the captured image, etc., it is affected by the shake information detection error or noise. A good restoration result cannot be obtained. Here, the case where the detection accuracy of the shake information is low is a case where the detection accuracy of an angular velocity sensor or the like that detects camera shake is low. Moreover, the case where there is noise in the photographed image is, for example, a case where white noise enters the photographed blurred image.

  Therefore, an object of the present invention is to improve a restoration result when restoring a signal using change information that causes a change in a signal such as an image.

  In order to solve the above-described problems, the signal processing apparatus of the present invention should be acquired from the output signal, which is a changed observation signal, in the process of signal measurement, observation, and / or recording, or the signal before change or originally acquired. And a processing unit that restores the ideal signal or its approximate signal (hereinafter referred to as an input signal). The processing unit further outputs the output signal using one or more types of known change functions. Processed into multiple change signals that have been changed once or multiple times, using processed change information obtained from known change functions and original change information that causes changes from input signals to output signals Perform restoration.

  According to the present invention, the effect of error or noise is reduced in the obtained processed original change information. Therefore, when a signal such as an image is restored using the processed original change information, the restoration result can be improved.

  In addition to the above-described invention, the signal processing apparatus according to another invention is a total change function obtained by superimposing a transfer function calculated from the original change information and a known change function. It is supposed to be. With this configuration, it is possible to set a comprehensive change function that is a kind of processed original change information.

  In addition to the above-described invention, the signal processing device according to another invention includes a detection unit that detects a disturbance, and the processed original change information includes an error caused by the disturbance detected by the detection unit, or It is intended to mitigate the effects of noise and / or errors or noise caused by what is inherent in the signal processing apparatus. With this configuration, the influence of dynamic change information in the process of signal measurement, observation, and recording performed by the signal processing device, and / or static change information caused by something inherent in the signal processing device. Can be reduced.

  In a signal processing device according to another invention, in addition to the above-described invention, the processing unit uses a change function based on the original change information as a known change function. With this configuration, the influence of the error of the original change information can be mainly reduced.

  In a signal processing device according to another invention, in addition to the above-described invention, the processing unit performs an inverse transformation process or a deconvolution operation process on a signal to be restored. With this configuration, for example, stable signal restoration can be performed by an existing mature technique such as a Wiener filter, a general inverse filter, or an iterative method, such as signal restoration by performing inverse transformation of a transfer function.

  In addition to the above-described invention, a signal processing apparatus according to another invention uses a signal as an image. As a result, even if an image change due to camera shake occurs, it is possible to restore from an output image in which a change such as deterioration has occurred to an input image in which there is no change such as deterioration.

  In a signal processing device according to another invention, in addition to the above-described invention, the original change information includes one or more of image blur information, image focus information, and optical information. Accordingly, when the original change information is the blur information, it is possible to reduce the influence of the blur information error or noise when restoring the blurred image. Further, when the original change information is the focus information of the image, it is possible to reduce the influence of the error or noise of the focus information of the image when restoring the out-of-focus image. Further, when the original change information is optical information, for example, when restoring a changed image due to optical aberration, it is possible to reduce the influence of errors or noise in the optical information. In addition, by including any two or more of these pieces of information in the original change information, for example, when restoring a change image with blurring and blurring, the influence of error or noise in blur information and image focus information is reduced. can do.

  In order to solve the above-described problem, the change information generation method of the present invention provides one or more types of original change information that is a factor of change obtained when shifting from a predetermined signal to a changed signal. Using known data.

  According to the present invention, the generated original change information is less affected by errors or noise. Therefore, when a signal such as an image is restored using the generated original change information, the restoration result can be improved.

  In order to solve the above-described problem, the change information generation method of the present invention provides one or more types of original change information that is a factor of change obtained when shifting from a predetermined signal to a changed signal. Are integrated, added, or multiplied.

  According to the present invention, the generated original change information includes original change information including an unknown amount of error or noise, and known data that can be treated as including no error or noise as change information. That component. By doing so, the error or noise contained in the original change information can be reduced, or the influence of the large error or noise can be reduced by reducing the uneven distribution of the error or noise. When a signal such as an image is restored using this, the restoration result can be improved.

  In order to solve the above-described problem, another change information generation method of the present invention includes original change information, which is a factor of change, and one or more types obtained when shifting from a predetermined signal to a changed signal. Generate known change data and multiple change signals obtained by further changing the change signal using the known data, and superimposing and integrating the original change information and the known data The integrated value is processed original change information for restoring the change signal from the change signal to a predetermined signal a plurality of times.

  According to this invention, the generated processed original change information includes original change information including an unknown amount of error or noise, and known data including no error or noise as change information, and its constituent elements Become. By doing so, the error or noise contained in the original change information can be reduced, or the uneven distribution of the error or noise can be reduced, and the influence of the large error or noise can be reduced. Further, by using the known data to further change the change signal to make the change signal a plurality of times, the uneven distribution of noise included in the change signal can be reduced. Therefore, when a signal such as an image is restored using the generated multiple-time change signal and the generated processed original change information, the restoration result can be improved.

  In the present invention, when a signal is restored using change information that causes a signal such as an image to change, the restoration result can be improved.

  Hereinafter, a signal processing apparatus according to an embodiment of the present invention that employs a change information generation method according to an embodiment of the present invention will be described with reference to the drawings. Although this signal processing device is a consumer camera, it may be a camera for other uses such as a surveillance camera, a television camera, a video camera, an endoscopic camera, a telescope, a microscope, and further an NMR photographing. The present invention can also be applied to devices other than cameras, such as diagnostic imaging devices, such as devices that measure signals.

  FIG. 1 shows an outline of the configuration of the signal processing apparatus 1. The signal processing apparatus 1 includes an image capturing unit 2 that captures an image of a person or a landscape, a control system unit 3 that drives the image capturing unit 2, an image signal that is captured by the change function processing described later and the image capturing unit 2. A processing unit 4 that performs the above processing, a recording unit 5 that records the image signal processed by the processing unit 4 or change information as necessary, and dynamic change information that becomes change information of an image change at the time of shooting. It has the detection part 6 to detect, and the static change information storage part 7 which preserve | saves static change information. When the signal processing device 1 is applied to a signal other than an image signal, the photographing unit 2 becomes a receiving unit 2 that receives various input signals such as an audio signal (hereinafter, the photographing unit 2 is appropriately used). And the receiving unit 2 are used properly).

  The photographing unit 2 includes a photographing optical system or an image sensor such as a CCD or C-MOS that converts light passing through the optical system into an electric signal, a circuit unit that converts the electric signal converted by the image sensor into an image signal, and the like. It is a part to prepare. The control system unit 3 controls each unit of the signal processing device 1 such as the imaging unit 2, the processing unit 4, the recording unit 5, the detection unit 6, and the static change information storage unit 7.

  The processing unit 4 is configured by an image processing processor, and is configured by hardware such as an ASIC (Application Specific Integrated Circuit). Or it is good also as a structure processed not by hardware like ASIC but by software. The processing unit 4 processes the image data photographed by the photographing unit 2. During this process, a total change function for signal (image) restoration processing is calculated from the dynamic change information and static change information, and a degraded (change) image is restored using the total change function. . Further, the processing unit 4 generates a sampling frequency for detecting vibrations such as camera shake to be detected and supplies the sampling frequency to the detection unit 6. Further, the processing unit 4 controls the start and end of vibration detection. When the signal processing device 1 is applied as a device other than the image processing device, the reception sensitivity of the receiving unit 2 can be changed according to the magnitude of the input signal or the like.

  The recording unit 5 is composed of a semiconductor memory, but a magnetic recording unit such as a hard disk drive or an optical recording unit such as a DVD may be employed. The recording unit 5 stores and records necessary data, for example, image signals that have not been restored yet, processed image signals, change information, and the like.

  The detection unit 6 detects dynamic change information generated in the process of measurement, observation, and recording. For example, as shown in FIG. 2, the speeds around the X axis and Y axis that are perpendicular to the Z axis, which is the optical axis of the signal processing device 1, are detected. If there is a camera shake at the time of shooting, the shot image becomes a blurred image. Such camera shake also causes movement in each direction in the X, Y, and Z directions and rotation around the Z axis. However, the most affected by each variation is the rotation around the Y axis and the X axis. Rotation around. These two variations are only slightly varied, and the captured image is greatly blurred. For this reason, in this embodiment, a PITCH (motion in the up and down (Y) direction) detection sensor and a YAW (movement in the left and right (X) direction) are used to detect blurring around the X axis and the Y axis in FIG. 3) a detection sensor and a ROLL (tilt in the left-right (X) direction) detection sensor. However, for the sake of completeness, an angular velocity sensor around the Z axis may be further added, or a sensor for detecting movement in the X direction or the Y direction may be further added. The sensor used may be an angular acceleration sensor instead of an angular velocity sensor. When the signal processing apparatus 1 is applied to a signal other than an image signal and the reception characteristic or the response characteristic of the signal processing system is affected by, for example, temperature or humidity, the detection unit 6 includes a thermometer or A hygrometer can be included.

  The static change information storage unit 7 stores static change information. This static change information is caused by information inherent in the signal processing apparatus 1 such as a point spread function due to aberration of the optical system, for example. When the signal processing apparatus 1 is applied to signals other than image signals, response characteristics that are known in advance, such as an impulse response of the entire signal processing system, can be stored in the static change information storage unit 7. Furthermore, since the temperature, humidity, etc. detected by the detection unit 6 may change the reception characteristics of the reception unit 2 or the characteristics of the entire system, the temperature characteristics, humidity characteristics, etc. can be used as static change information. .

Next, an outline of a method for creating restoration data from a change signal in the processing unit 4 of the signal processing apparatus 1 according to the present embodiment configured as described above will be described. FIG. 3 shows the relationship between the input signal in, the observation system transfer function g, the noise n, and the observed output signal out. The input signal in is received by the receiving unit (imaging unit 2) of the observation system and output as the output signal out. If no deterioration (change) or the like occurs between reception and output, the output signal out is completely equal to the input signal in. However, in practice, the output signal out always changes due to a delay in tracking the input signal. Such deterioration (change) is defined as a transfer function g of the signal processing system. In addition to the change, noise n and the like further enter. That is, the output signal out is obtained by adding noise n to the convolution of the input signal in and the transfer function g (Equation (1)).
out = in * g + n (1)
* Represents a convolution operation. same as below.

In the present embodiment, the input signal in corresponds to an ideal image that should have been originally acquired. The output signal out corresponds to an observation signal (photographed image) that has changed in the process of signal measurement, observation, and / or recording. The transfer function g corresponds to the original change information. Here, unless the transfer function g is acquired by any method, the input signal in or its approximate signal cannot be obtained from the output signal out. Therefore, the static change function gs that has been known in advance among the original change information (transfer function g), such as a point spread function due to aberrations of the optical system, is obtained from the static change information storage unit 7 described above. To do. Among the original change information, the dynamic change function gd due to disturbance at the time of acquisition of the input signal in is detected by the detection unit 6 and calculated and acquired by the processing unit 4. The dynamic change function gd is acquired by, for example, detecting camera shake as trajectory data by an angular velocity sensor included in the detection unit 6 and calculating the processing unit 4 based on the trajectory data. At this time, the transfer function g of the entire observation system is a convolution of the static change function gs and the dynamic change function gd (formula (2)). However, the signal processing apparatus 1 does not consider static change information such as optical aberration when only the image change due to the shake is a problem, but considers only the dynamic change function gd as shown in the equation (3). g can be obtained. Hereinafter, the transfer function obtained by the equation (3) is represented as g.
g = gs * gd (2)
g = gd (3)

  Here, as described above, when a disturbance is detected by the detection unit 6, a normal error occurs and noise is included in the detection result. Therefore, the transfer function g includes an error from the original transfer function or noise. The smaller the influence of this error or noise, the better the result of the restoration process. A method for reducing the influence of the error or noise will be described below.

<First processing method>
A method of creating restoration data when the processing unit 4 uses the transfer function g based on the original change information which is a kind of known change function as it is will be described with reference to FIGS. 1, 3 and 4. FIG. In this example, the transfer function g is treated as the first change function g_1. The input signal in is photographed by the photographing unit 2. The captured image signal is sent to the processing unit 4 as an output signal out. The original change information is the shake information at the time of shooting, and the detection unit 6 detects the camera shake as the information of the shake locus at the time of shooting using the angular velocity sensor, calculates the transfer function g, that is, the first change function g_1, and the processing unit. Send to 4.

In the restoration data creation sequence, the following processing is performed. A first change function g_1 for changing the output signal out with a known change function is calculated (step S101). Here, the transfer function g is employed as the first change function g_1. Next, the output signal out is further changed by the first change function g_1 to obtain a change signal once. Therefore, a convolution operation (equation (4)) between the output signal out and the first change function g_1 is performed to calculate a change signal out_1 once (step S102).
out_1 = out * g_1 (4)

Next, a convolution operation (formula (5)) is performed on the transfer function g, which is the original change information, and the first change function g_1, which is the one-time change information, and an overall transfer function g_all, which is a type of processed original change information, is calculated. (Step S103). The obtained once-change signal out_1 is used as a signal to be restored, and the restoration process is performed using the total transfer function g_all (step S104).
g_all = g * g_1 (5)

This will be further described with reference to FIG. As shown in FIG. 5A, the change signal out_1 is obtained once from the input signal in. In the restoration process, the restoration process is performed assuming that there is an input / output relationship as shown in FIG. That is, the following expression (6) is derived from the above expressions (1), (4), and (5).
out_1 = out * g_1 = (in * g + n) * g_1 = in * g_all + n * g_1 (6)

Here, the transfer function g and the total transfer function g_all are compared. Since the transfer function g includes a detection error in the detection unit 6, there is an error between the unknown correct transfer function and the obtained transfer function g. The error is δ, and the ratio of the error δ included in the transfer function g is e. e is derived from equation (7). The one-time change signal out_1 is obtained by changing the output signal out with a first change function g_1 which is a known transfer function g. There is no error when this change is made. Therefore, the error included in the total transfer function g_all remains δ. If the ratio of errors included in the total transfer function g_all is e_all, Expression (8) is established. Then, the ratio of the error δ contained in e_all becomes smaller than that of e. Therefore, the accuracy between the signal out_1 obtained by further changing the output signal out and the total transfer function g_all is improved. Therefore, the influence of the error of the original change information can be reduced by performing the restoration process using the total transfer function g_all.
e = | δ | / | g | (7)
e_all = | δ | / | g_all | = | δ | / | g * g_1 | (8)

  Further, when comparing the noise components of Expression (1) and Expression (6), since the noise component n * g_1 of the once-change signal out_1 changes and diffuses, the noise n included in the output signal out The ratio of noise included in the once-change signal out_1 is lower than the ratio of. Therefore, the influence of noise components in the restoration process can be reduced. Therefore, by performing restoration processing using this, it is possible to reduce the influence of the error or noise of the original change information, so that the restoration result can be improved. The change of the output signal out is targeted for the shake that is the dynamic change information, but is transmitted from the impulse response of the entire signal processing system, which is the static change information, or both the dynamic change information and the static change information The function g may be obtained.

<Second processing method>
In the first embodiment, the transfer function g based on the original change information, which is a known change function, is used as it is as the first change function g_1. However, a transfer function g based on the original change information may be processed or used. Processing in that case will be described with reference to FIG. For example, when the original change information is shaken, the shake is expressed by a trajectory and a weight. Therefore, among the detected trajectories and weights, the blur trajectory is used as it is, and the first change function g_1 is calculated as a shake in which the weight becomes constant by changing the weight (step S101), and using the first change function out_1 (Step S102), the total transfer function g_all is calculated (step S103), and the once-change signal out_1 is set as a signal to be restored, and restoration processing such as inverse transformation processing (step S104) is performed. good. When the impulse response of the entire signal processing system is targeted as the original change information, the first change function g_1 may be a response characteristic that provides a constant output without changing the length of the impulse response. Such processing is equivalent to making the weights constant.

  In addition, when a shake is detected in the detection unit 6, the vibration of the detected shake is subjected to frequency decomposition by Fourier transform or the like, and if there is a frequency band in which the detection accuracy of the detection unit 6 is previously known to be low, the detected shake By creating the first change function g_1 using the vibration in the band, the influence of the error factor can be effectively reduced for the portion where the detection error is large. For example, when the offset voltage of the shake detection sensor is unstable, it causes an error in the transfer function of the signal processing system. However, the vibration of the detected shake is frequency-resolved and the first change function g_1 is calculated from the DC component. By doing so, it is possible to reduce the influence of error factors due to instability of the offset voltage.

<Third processing method>
When there is noise in the output signal out and the noise greatly affects the restoration result, the first change function is independent of the transfer function g of the signal processing system. It is preferable to do this. In the case of an image signal, for example, data of a specific pixel shown as a shaded portion in FIG. 6A is spread to eight adjacent peripheral pixels (FIG. 6B), or adjacent in four diagonal directions. A transfer function having one of the functions of spreading to peripheral pixels (FIG. 6C) and further spreading to peripheral pixels adjacent in four vertical and horizontal directions (FIG. 6D) is defined as a first change function g_1. . In this method, when there is noise when shooting an image and the noise is unevenly distributed to a specific pixel, the influence of the error or noise is reduced by reducing the uneven distribution of the error due to the noise. can do.

<Fourth processing method>
Since there is an error in the original change information, there is an error in the transfer function g obtained therefrom, and when there is noise in the output signal out, an example of processing for reducing the influence of both the error and the noise is shown in FIG. Will be described. First, the first change function g_1 for reducing the influence of the error of the transfer function g serving as the original change function is calculated (step S201), and the change signal out_1 is calculated once using the first change function g_1 (step S202). Up to this point, it is the same as the first embodiment or the second embodiment. That is, formula (1) or formula (6) is calculated.

Next, a second change function g_2 for reducing the influence of noise is calculated (step S203). This second change function g_2 is, for example, the transfer function of the third embodiment. Next, the twice-change signal out_2 is calculated by changing the once-change signal out_1 with the second change function g_2 (step S204). Here, Equation (9) is calculated.
out_2 = out_1 * g_2 (9)

Next, the original change function g, the first change function g_1, and the second change function g_2 are convolved to calculate the total change function g_all (step S205). Here, Equation (10) is calculated.
g_all = g * g_1 * g_2 (10)

  The obtained twice-change signal out_2 is used as a signal to be restored, and the restoration process is performed using the overall change function g_all (step S206). Here, the two-time change signal may be calculated using a composite change function g_12 obtained by convolving the first change function g_1 and the second change function g_2. This is shown in FIG.

First, the first change function g_1 and the second change function g_2 are calculated (steps S301 and S302). Next, the composite change function g_12 is calculated by calculating Expression (11) (step S303). The output signal out is changed by the composite change function g_12, and the twice-change signal out_2 is calculated (step S304). Here, the equation (12) is calculated. Next, the original change function g and the composite change function g_12 are convolved to calculate the total change function g_all (step S305). Here, Equation (13) is calculated. Using the obtained twice-change signal out_2 and the total change function g_all, a restoration process by inverse transformation or the like is performed (step S306).
g — 12 = g1 * g2 (11)
out_2 = out * g_12 (12)
g_all = g * g_12 (13)

The signal processing apparatus 1 according to the present embodiment has been described above, but various modifications can be made without departing from the gist of the present invention. For example, as the processing unit 4, the following method shown in FIG. First prepared arbitrary signal data _{I 0} (step S401). The original change information G is superimposed and integrated on the arbitrary signal data I ₀ (step S402), and then the known data s1 that is a known change function is further superimposed and integrated to generate comparison data I ₀ ″ (step S403). ). Thereafter, the changed output signal data “Img ′ * s1” obtained by superimposing the output signal Img ′ and the known data s1 is compared with the comparison data I ₀ ″ (step S404). Then, using the processed original change information obtained by superimposing the original change information G and the known data s1 on the obtained difference data δ ′, the arbitrary signal data I ₀ , or the arbitrary signal data I ₀ and the original By distributing to either one of the superimposed integral values I ₀ ′ with the change information G (arbitrary signal data I _{0 in} FIG. 9), the restored data I _{0 + n} is generated (step S406). Here, “k” is a distribution ratio based on the processed change information. The restored data I _{0 + n} is used in place of the arbitrary signal data I ₀ or the superimposed integral value I ₀ ′ to generate again the comparison data I ₀ ″ and perform a series of processing such as comparison processing. Then, iterative processing is repeated until the absolute value of the difference data δ ′ becomes less than a predetermined value (step S405). The restored data I _{0 + n} finally obtained by this processing can be estimated as the input signal Img which is an ideal image (input signal in). The restoration result can also be improved by such repeated processing.

  In the present embodiment, processing that considers static change information is not performed. However, when the influence of an error or noise caused by what is inherently present in the signal processing apparatus 1 is known in advance, the transfer function obtained by the above equation (2) is taken into account that error or noise. It is possible to perform signal restoration processing with g as a symbol. For example, an error or noise generated due to the inherent presence in the signal processing device 1 detects a detection error or a shake when there is an error in the mounting angle of a gyro or the like that detects dynamic source change information. This is an error or the like when the gyro reference voltage (offset voltage) deviates from a set value when a gyro is used for the sensor.

  In the present embodiment, the original change information g and G are used as known data. However, it goes without saying that data that can be prepared before obtaining the output signal can be used as known data for changing the signal.

  In the present embodiment, the processed original change information is obtained by superimposing original change information g, G and known data for changing an image, and the original change information g, G and the known data are combined. In addition, or by multiplying, processed source change information may be generated.

  In addition, “change”, which is a word used for original change information, processed original change information, and comprehensive change function, includes not only deterioration but also information that improves a signal (image) contrary to deterioration. .

  In the above-described embodiment, the restoration target is image data. However, these restore processing concepts and techniques can be applied to any data restore process. For example, it can be applied to restoration of digital audio data.

It is a block diagram which shows the main structures of the signal processing apparatus which concerns on embodiment of this invention. It is an external appearance perspective view which shows the outline | summary of the signal processing apparatus shown in FIG. 1, and is a figure for demonstrating the arrangement position of an angular velocity sensor. It is a figure which shows the outline | summary of the processing method performed in the process part of the signal processing apparatus shown in FIG. 1, and is a figure which shows the relationship between an input signal, the transfer function of an observation system, noise, and the output signal observed. It is a processing flowchart for demonstrating the data creation sequence for a restoration used as the 1st or 2nd processing method implemented with the signal processing apparatus which concerns on embodiment of this invention. It is a figure explaining the detail of the 1st processing method which the process part of the signal processing apparatus which concerns on embodiment of this invention performs, (A) is a figure which shows the process in which a change signal is obtained once from an input signal. B) is a diagram illustrating the concept of the restoration process. It is a figure for demonstrating the 3rd processing method which the process part of the signal processing apparatus which concerns on embodiment of this invention performs, and it is the influence of noise by spreading the noise unevenly distributed in a specific pixel to a surrounding pixel. It is a figure showing a mode that it reduces. It is a processing flowchart for demonstrating the restoration data creation sequence used as the 4th processing method which the process part of the signal processing apparatus which concerns on embodiment of this invention performs. It is a processing flow figure for explaining the data creation sequence for restoration used as the modification of the 4th processing method which the processing part of the signal processor concerning an embodiment of the invention performs. It is a processing flowchart for demonstrating the processing routine which concerns on the image restoration processing method (iteration process) which is another example of the processing method performed by the process part of the signal processing apparatus which concerns on embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Signal processing apparatus 2 Imaging | photography part (receiver)
3 Control system unit 4 Processing unit 5 Recording unit 6 Detection unit 7 Static change information storage unit in input signal out output signal g transfer function (original change information, known change function)
g_1 first change function (known change function)
g_2 Second change function (known change function)
out_1 Single change signal (Multiple change signal)
out_2 Twice change signal (multiple change signal)
g_all Processed original change information (total transfer function)

Claims (10)

From the output signal, which is an observation signal that has changed in the process of signal measurement, observation, and / or recording, the signal before the change or the ideal signal that should have been originally acquired, or its approximate signal (hereinafter referred to as the input signal) In a signal processing apparatus having a processing unit for performing restoration to
The processing unit uses one or more types of known change functions to process the output signal into a multiple change signal that is changed once or multiple times, and the known change function and the input signal A signal processing apparatus that performs restoration using processed original change information obtained from original change information that causes a change from the output signal to the output signal.   The signal processing according to claim 1, wherein the processed original change information is a comprehensive change function obtained by superimposing a transfer function calculated from the original change information and the known change function. apparatus. The signal processing device has a detection unit for detecting disturbance,
The processed original change information is the influence of the error or noise caused by the disturbance detected by the detection unit and / or the error or noise generated due to the inherent presence in the signal processing device. 2. The signal processing apparatus according to claim 1, wherein the signal processing apparatus is for reducing an influence.   The signal processing apparatus according to claim 1, wherein the processing unit uses a change function based on the original change information as the known change function.   The signal processing apparatus according to claim 1, wherein the processing unit performs an inverse transform process or a deconvolution operation process on a signal to be restored.   The signal processing apparatus according to claim 1, wherein the signal is an image.   The signal processing apparatus according to claim 6, wherein the original change information includes at least one of image blur information, image focus information, and optical information.   Generation of change information characterized by using one or a plurality of types of known data for the original change information that causes the change, which is obtained when a change signal is changed from a predetermined signal Method.   To superimpose, add, or multiply one or more types of known data to the original change information that causes the change, obtained when shifting from a predetermined signal to a change signal that has changed. A method of generating characteristic change information.   The original change information that causes the change, the one or more kinds of known data, and the change signal using the known data, which are obtained when shifting from a predetermined signal to a changed signal Is generated by further changing the signal, and the original change information and the known data are superimposed and integrated, and the obtained superimposed integration value is changed from the multiple-time change signal to the predetermined signal. A method of generating change information, characterized by using processed original change information for restoration.

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