An image sensor for capturing a color image is disclosed having a two-dimensional array having first and second groups of pixels wherein pixels from the first group of pixels have narrower spectral photoresponses than pixels from the second group of pixels and wherein the first group of pixels has individual pixels that have spectral photoresponses that correspond to a set of at least two colors, with the placement of the first and second groups of pixels defining a pattern that has a minimal repeating unit including at least six pixels with at least some rows or columns of the minimal repeating unit composed only of pixels from the second group of pixels, and including ways to combine similarly positioned pixels from at least two adjacent minimal repeating units.

Image sensor with improved light sensitivity

An electronic endoscope system according to the present invention has a video-scope that has an image sensor, and a light source unit that is capable of selectively emitting normal-light and excitation-light. The electronic endoscope system further has a signal processor and a display processor. The signal processor generates normal color image signals, which corresponds to the normal color image, on the basis of the normal image-pixel signals. Similarly, the signal processor generates auto-fluorescent image signals corresponding to the auto-fluorescent image on the basis of the auto-fluorescent image-pixel signals, and generates diagnosis color image signals corresponding to the diagnosis color image on the basis of the normal color image signals and the auto-fluorescent image signals. The display processor processes the normal color image signals, the auto-fluorescent image signals, and the diagnosis color image signals so as simultaneously to display a normal color movie-image, an auto-fluorescent movie-image, and a diagnosis color movie-image.

Electronic endoscope system

In one aspect of the present invention, a method is provided for using a display having a predetermined display resolution to show out of focus areas in an archival image having a greater resolution than the predetermined display resolution In this method, a verification image sized for presentation on the display, is provided Portions of the archival image that are out of focus are identified The verification image is blurred so that portions of the verification image that correspond to out of focus portions of the archival image appear out of focus when the verification image is presented on the display In another aspect a camera system is provided having a source of an archival image with a predetermined resolution and a verification display having an image display resolution that is lower than the predetermined resolution of the archival image A signal processor is provided, with said signal processor processing the archival image to identify out of focus portions of the archival image and to form a verification image formatted for presentation on the verification display said signal processor further modifying the appearance of the verification image so that portions of the verification image that correlate to identified portions of the archival image appear out of focus when the modified verification image is presented on the verification display

Method and camera system for blurring portions of a verification image to show out of focus areas in a captured archival image

Systems and methods for determining a set of sub-classifiers for a detector of an object detection program are presented. According to one embodiment, the system may include a candidate coefficient-subset creation module, a training module in communication with the candidate coefficient-subset creation module, and a sub-classifier selection module in communication with the training module. The candidate coefficient-subset creation module may create a plurality of candidate subsets of coefficients. The coefficients are the result of a transform operation performed on a two-dimensional (2D) digitized image, and represent corresponding visual information from the 2D image that is localized in space, frequency, and orientation. The training module may train a sub-classifier for each of the plurality of candidate subsets of coefficients. The sub-classifier selection module may select certain of the plurality of sub-classifiers. The selected sub-classifiers may comprise the components of the detector. Also presented are systems and methods for detecting instances of an object in a 2D (two-dimensional) image.

Object finder for two-dimensional images, and system for determining a set of sub-classifiers composing an object finder

A method of focusing a digital camera module with an image sensor including capturing an image of a test target with the digital camera module, determining a focus quality of the image with the image sensor, outputting a signal related to the focus quality of the image from the digital camera module to a focusing station external to the digital camera module, and determining whether a position of a lens from the image sensor within the digital camera module should be altered to improve a focus quality of subsequently captured images.

System and method for focusing a digital camera

A noise elimination apparatus and method enable effective elimination of noise on each line in an image captured by a CCD provided with a Bayer-type color filter. A graduation device obtains the quantity of graduation for a target picture element by obtaining the difference between the mean value of the value of the target pixel and the value of a pixel around the target pixel and the value of the target pixel. A high frequency component detector detects the high frequency component of the target pixel using Laplacian filter based upon the target pixel and each of the pixels immediately adjacent to said target pixel are input. A high frequency component can be detected without being influenced by noise on each line by using a filter based upon each of the pixels immediately adjacent to said target pixel. Noise on each line can be effectively eliminated by adding the optimum quantity of graduation based upon the absolute value of the high frequency component detected by the high frequency component detector to the value of the target pixel.

Apparatus and method for eliminating imaging sensor line noise

An image is divided into a plurality of subdivision areas. A focus evaluation value representative of the high frequency component contained in the electrical signal from the CCD is calculated for each of the subdivision areas. The object distance is calculated for the respective subdivision areas based on the focus evaluation value. A target object is extracted based on the calculated object distance. The target object is focused. During the focusing operation, when a new object having an object distance smaller than that of the target object is detected in any of remote subdivision areas which have an object distance larger than that of the target object, the target object is re-selected.

Method of automatic object detection in image

A brightness threshold value calculation unit figures out a brightness threshold value on the basis of a brightness average value of all blocks and the brightness of a maximum brightness block determined by a maximum brightness block search unit. Block average value calculation units extract blocks corresponding thereto and find average values of representative values of the extracted blocks. At that time, subjects of extraction by the block average value calculation units are limited to blocks having a higher brightness than the brightness threshold value among all the blocks. A white balance gain is then determined from the thus obtained block average values. This configuration achieves a white balance which responds better to light sources since the white balance gain is not affected by values of dark blocks which are considered not to well reflect the color of light from the light sources.

Auto white balance apparatus

PROBLEM TO BE SOLVED: To realize a more natural color hue in a device for obtaining white balance based on the mean value of pixels in each block of an image. SOLUTION: A luminance threshold calculation part 14 finds out a luminance threshold based on the mean value of the luminance of all blocks and the luminance of a highest luminance block found out by a maximum luminance block searching part 12. Each of block mean value calculation parts 16 to 22 extracts its corresponding block and finds out the mean value of representative values of the extracted block. Each of these calculation parts 16 to 22 extracts only blocks having luminance higher than the luminance threshold out of all blocks. Then white balance gain is found out based on the respective block mean values found out by respective calculation parts 16 to 22. Since the value of a dark block to which the color of light from a light source may not be sufficiently reflected does not exert influence upon the white balance gain in the constitution, white balance more corresponding to the light source can be realized.

Auto-white balance device

An auto white balancing apparatus includes a block split circuit for splitting an image into a plurality of blocks; a representative color calculating circuit which for each split block, derives a representative color of each block on the basis of pixel values within each block; and a block reliability estimating circuit which for each block and for each light source determines the distance between color difference components of the color of a white object under each light source and color difference components of the representative color of each block, to thereby estimate a reliability signal with which each light source lights a scene of each block on the basis of the distances. The auto white balancing apparatus also includes a light source contribution component estimating circuit which for each light source, weights and averages the representative color of each block in accordance with the reliability signal of each light source upon each block, to thereby estimate components of contribution of each light source to the entire image; and a total reliability estimating circuit which for each light source, totals up the reliability signal of each light source upon each block over all blocks contained within the image, to thereby estimate the reliability signal of each light source in the entire image. The auto white balancing apparatus further includes a lighting color estimating circuit for weighting and averaging components of contribution of each light source to the entire image estimated by the light source contribution component estimating circuit, in accordance with the reliability signal of each light source upon the entire image estimated by the total reliability estimating circuit, to thereby estimate the color of lighting which lights the scene of the entire image; and a white balancing circuit for executing white balance processing of each pixel of the image so as to cancel the lighting color estimated.

Toshiki Miyano

Papers

Apparatus and method for eliminating imaging sensor line noise

Method of automatic object detection in image

Auto white balance apparatus

Auto-white balance device

Auto white balancing apparatus and method