A signal processing device includes a signal output circuit, a controller, and a corrector. The signal output circuit outputs a signal according to a physical quantity being input. The controller controls the signal output circuit. The corrector corrects a signal to be corrected. The signal to be corrected is output from the signal output circuit. The signal output circuit selectively performs one of first operation of outputting a characteristic signal that indicates characteristics of the signal output circuit and second operation of outputting a pseudo signal that is generated spuriously, according to control of the controller. The corrector corrects the signal to be corrected based on one of the characteristic signal and the pseudo signal output from the signal output circuit.

A signal processing device includes a signal output circuit, a controller, and a corrector. The signal output circuit outputs a signal according to a physical quantity being input. The controller controls the signal output circuit. The corrector corrects a signal to be corrected. The signal to be corrected is output from the signal output circuit. The signal output circuit selectively performs one of first operation of outputting a characteristic signal that indicates characteristics of the signal output circuit and second operation of outputting a pseudo signal that is generated spuriously, according to control of the controller. The corrector corrects the signal to be corrected based on one of the characteristic signal and the pseudo signal output from the signal output circuit.

An image processing apparatus includes: a first inverter to output binary image data having first resolution, as image data having pixel values that are inverted or image data having unprocessed pixel values, in accordance with an inversion signal; a thinning processor to convert the image data output from the first inverter from the first resolution to second resolution and perform a thinning process of thinning pixels of edge portions of the image data in units of the second resolution; and a second inverter to output the image data having the second resolution for which the thinning process is performed, as image data having pixel values that are inverted or image data having unprocessed pixel values, in accordance with the inversion signal.

An image processing device includes: a first matching circuit to determine whether an image matrix of image data of a first resolution matches a first pattern, and output a first determination result; a first converting circuit to, if the image matrix matches the first pattern, replace a target pixel of the image matrix with a first pixel pattern of a second resolution, and output first image data of the second resolution; a second converting circuit to convert the image data of the first resolution into image data of the second resolution, and output second image data of the second resolution; a detecting circuit to detect whether the target pixel is included in a fine line structure, and output a detection result; and a selecting circuit to output one of the first image data and the second image data based on the first determination result and the detection result.

An image processing method separates an input image into a skeleton component, and residual component. In the method a local variation amount, which is a variation amount between a target pixel and a pixel adjacent to the target pixel, is calculated; a skeleton component extraction filter weight is calculated based on the local variation amount; an image feature amount of a gradient direction of a pixel value around the target pixel, and an image feature amount of a gradient strength of the pixel value around the target pixel, are calculated; the skeleton component extraction filter weight is corrected based on these image feature amount; a skeleton component extraction filter coefficient is calculated based on the corrected skeleton component extraction filter weight; and the skeleton component is extracted by applying skeleton component extraction filtering to the target pixel using the calculated skeleton component extraction filter coefficient.

Provided is an image processing apparatus for correcting blinking defect noise included in image data generated by an image sensor, the image sensor including pixels arranged two-dimensionally and read-out circuits configured to read out a pixel value. The image processing apparatus is configured to: acquire noise information that associates the pixel value with positional information of the read-out circuits or positional information of each of the pixels, and with feature data related to blinking defect noise attributed to the read-out circuits; determine whether the blinking defect noise occurs on a pixel of interest based on the noise information; calculate candidate values indicating a correction amount for correcting the blinking defect noise based on the noise information and a pixel value of the pixel of interest if the blinking defect noise occurs; and correct the pixel value of the pixel of interest based on the candidate values.

Determination information is obtained to determine a degradation characteristic of sharpness of an image formed by an image forming apparatus. One of a plurality of recovery processing parameters used to recover sharpness of an image is selected based on the determination information, and characteristics of the plurality of recovery processing parameters are different from each other. Recovery processing of sharpness is performed on image data using the selected recovery processing parameter. When the degradation characteristics of sharpness are visually and substantially the same, the same recovery processing parameter is selected.

The present invention provides an image processing method, an image processing device, and an image processing program which require low computing costs and with which it is possible to minimize noise amplification and halo generation caused by HDR. An image processing device according to one embodiment of the present invention has: a multi-resolution image generation means for generating a multi-resolution image; a correction amount calculation means for calculating a brightness correction amount on the basis of a lowest-resolution image of the multi-resolution image, a differential image between adjacent resolutions of the multi-resolution image, and edge information calculated at each resolution of the multi-resolution image; and a noise suppression means for calculating, on the basis of the lowest-resolution image, the differential image between adjacent resolutions, the edge information, and the brightness correction amount, an image after brightness correction in which a noise component is suppressed.

A signal processing apparatus includes an acquisition unit that acquires input data and detection target data, a noise strength setting unit that sets a noise strength K used to a predetermined stochastic resonance processing and a stochastic resonance processing unit that performs the predetermined stochastic resonance processing and outputs processed data. The predetermined stochastic resonance processing is a processing based on a formula in which processed data J(x) is represented by I(x), the noise strength K and the threshold value T and the processed data J(x) corresponds to a result in a case where M is infinite in the following formula,

[00001]$J\left(x\right)=\frac{1}{M}.Math.\underset{m=1}{\overset{M}{.Math.}}.Math.j\left(x,m\right).$

The noise strength setting unit sets the noise strength based on a function of a correlation coefficient between the result of the predetermined stochastic resonance processing and the detection target data and the noise strength K.

A signal processing apparatus includes a unit configured to generate noise cut data by deducting a predetermined noise value from values of respective signals constituting input data and a stochastic resonance processing unit configured to subject the noise cut data to a predetermined stochastic resonance processing. The predetermined stochastic resonance processing is processing to output, in a method of synthesizing a result of parallelly performing steps of adding new noise to the noise cut data to subject the resultant data to a binary processing, a value obtained in a case where the parallel number is infinite.