An image forming apparatus outputs a tone chart for calibration by a printer, reads the output tone chart by a scanner, determines whether data on a sheet is affected by a surface shape of the sheet based on the read tone chart, corrects data on a white area of the read chart based on a result of the determination, and executes calibration using the corrected data.

An image that enables proper object recognition is generated. An image processing device includes an image processing unit that processes an image. The image processing unit included in this image processing device corrects the level of a pixel constituting the image. That is, the image processing unit corrects the level of a target pixel constituting the image on the basis of a low-frequency component in a peripheral image of a pixel constituting the target image. Here, the peripheral image is made up of a plurality of pixels that includes the target pixel and is located around the target pixel.

The present disclosure relates to a method performed by a deviation analyzing system (1) for black level drift assessment of a digital camera image sensor (21). The deviation analyzing system measures (1001) for pixels of an image captured by the image sensor, a respective luminance value and corresponding chromaticity value of each pixel. The deviation analyzing system further determines (1002) a respective average chromaticity value for differing luminance levels of the measured luminance values, based on for each luminance level averaging the corresponding measured chromaticity values. Moreover, the deviation analyzing system determines (1003), when the respective average chromaticity values of a range (4) of luminance levels indicate—to a predeterminable extent—chromaticity deviations (5) from the respective average chromaticity values (6) of other luminance levels (7), that a black level setting of the image sensor is drifted from a true black level.

The disclosure also relates to a deviation analyzing system in accordance with the foregoing, a digital camera comprising such a deviation analyzing system, and a respective corresponding computer program product and non-volatile computer readable storage medium.

A method and computer device for determining a spatial luminance distribution over at least one image of a scene illuminated by at least one illuminant (121) are provided. The image comprises RGB channels. A linear combination of the RGB channels is applied to determine the luminance distribution. The linear combination has a set of coefficients comprising a respective coefficient for each of the RGB channels. The coefficients are determined by identifying a spectral power distribution, SPD, of the at least one illuminant and performing a search to determine values of the set of coefficients that minimise a spectral mismatch between: a) the identified SPD weighted by the linear combination; and b) the identified SPD weighted by a luminosity function.

There are provided a printing system, a method of generating a halftone processing rule, a method of acquiring a characteristic parameter, image processing device and method, a halftone processing rule, a halftone image, a method of manufacturing a printed material, an ink jet printing system, and a program which are capable of reducing an operation load of a user and acquiring a halftone processing rule appropriate for the printing system. A characteristic parameter acquisition chart including a pattern for acquiring characteristic parameters related to characteristics of the printing system is output, and the output characteristic parameter acquisition chart is read by image reading means. The characteristic parameters are acquired by analyzing the read image of the characteristic parameter acquisition chart, and halftone processing rules that define the processing contents of halftone processes used in the printing system are generated based on the acquired characteristic parameters.

Image analysis and processing may include a multiple-tone-control (MTC) unit configured to obtain a tone-control gain lookup table, a plurality of MTC gain lookup tables, wherein the input image is divided into a plurality of blocks and wherein the plurality of MTC gain lookup tables includes a respective MTC gain lookup table corresponding to each respective block from the plurality of blocks, MTC grid parameters, MTC weighting parameters, a tone-control gain based on the tone-control gain lookup table, a MTC gain based on at least one MTC gain lookup table from the plurality of MTC gain lookup tables, the MTC grid parameters, and the MTC weighting parameters, and an output value based on the tone-control gain and the MTC gain.

An image processing device that corrects an image captured by an imaging sensor is capable of setting an exposure condition for each of a plurality of regions and includes an acquisition unit configured to acquire the image by setting the exposure condition for each region in the imaging sensor, a derivation unit configured, regarding a boundary between a region of interest and at least one adjacent region adjacent to the region of interest in the image, to derive a correction amount in the region of interest based on pixel values of a boundary pixel group in contact with the boundary included in the region of interest and pixel values of a boundary pixel group in contact with the boundary included in the adjacent region, and a correction unit configured to correct pixel values of pixels in the region of interest based on the derived correction amount.

On a recording sheet of a first size, an image combined with gradation patches of a plurality of colors is printed, on a recording sheet of a second size smaller than the first size, images combined with the gradation patches of the plurality of colors are divided and printed into a plurality of recording sheets, color measurement is performed on each of the gradation patches, and gradation correction data is generated.

A determination unit determines whether a difference between a maximum value and a minimum value of pixel values of a plurality of pixels in a region of interest in N-gradation multi-valued data, where N≥4, representing the pixel values of the plurality of pixels is less than a determination threshold value. A generation unit generates M-gradation quantization data represented by an M-gradation quantization value, where 3≤M<N, based on the N-gradation multi-valued data and the determination. In a case where the determination unit determines that the difference is less than the determination threshold value, the generation unit generates the M-gradation quantization data so that each of the plurality of pixels corresponding to the region has a value that is one of two consecutive values of the M-gradation quantization values in the generated M-gradation quantization data.

A determination unit determines whether a difference between a maximum value and a minimum value of pixel values of a plurality of pixels in a region of interest in N-gradation multi-valued data, where N≥4, representing the pixel values of the plurality of pixels is less than a determination threshold value. A generation unit generates M-gradation quantization data represented by an M-gradation quantization value, where 3≤M<N, based on the N-gradation multi-valued data and the determination. In a case where the determination unit determines that the difference is less than the determination threshold value, the generation unit generates the M-gradation quantization data so that each of the plurality of pixels corresponding to the region has a value that is one of two consecutive values of the M-gradation quantization values in the generated M-gradation quantization data.