Altek Corporation

Altek Semiconductor Corp.

Shih-Yuan Peng

Hong-Long Chou

Yun-Chin Li

Hsin-Te Wang

Hsu-Lien Huang

Kuo-Ming Lai

Shu-Chun Cheng

Chung-Ta Wu

Ming-Jiun Liaw

Wen-Yan Chang

Chia-Yu Wu

Kai-Yu Tseng

Shan-Lung Chao

A dual sensor imaging system and a privacy protection imaging method thereof are provided. The system is configured to control at least one color sensor and at least one IR sensor to respectively capture multiple color images and multiple IR images by adopting multiple exposure conditions adapted for an imaging scene, adaptively select a combination of the color image and the IR image that can reveal details of the imaging scene, detect a feature area with features of a target of interest in the color image, and fuse the color image and the IR image to generate a fusion image with the details of the imaging scene, and crop an image of the feature area of the fusion image to be replaced with an image not belonging to the IR image, so as to generate a scene image.

Dual sensor imaging system and privacy protection imaging method thereof

A dual sensor imaging system and an imaging method thereof are provided. The method includes: identifying an imaging scene; controlling a color sensor and an IR sensor to respectively capture color images and IR images by adopting capturing conditions suitable for the imaging scene; calculating a signal-to-noise ratio (SNR) difference between each color image and the IR images, and a luminance mean value of each color image; selecting the color image and IR image captured under capturing conditions of having the SNR difference less than an SNR threshold and the luminance mean value greater than a luminance threshold to execute a feature domain transformation to extract partial details of the imaging scene; and fusing the selected color image and IR image to adjust the partial details of the color image according to a guidance of the partial details of the IR image to obtain a scene image with full details.

Dual sensor imaging system and imaging method thereof

A dual sensor imaging system and a depth map calculation method thereof are provided. The dual sensor imaging system includes at least one color sensor, at least one infrared ray (IR) sensor, a storage device, and a processor. The processor is configured to load and execute a computer program stored in the storage device to: control the color sensor and the IR sensor to respectively capture multiple color images and multiple IR images by adopting multiple exposure conditions suitable for an imaging scene, adaptively select a combination of the color image and the IR image that are comparable to each other from the color images and the IR images; and calculate a depth map of the imaging scene by using the selected color image and IR image.

Dual sensor imaging system and depth map calculation method thereof

A dual sensor imaging system and an imaging method thereof are provided. The dual sensor imaging system includes at least one color sensor, at least one infrared ray (IR) sensor, a storage device, and a processor. The processor is configured to load and execute a computer program stored in the storage device to: identify an imaging scene of the dual sensor imaging system; control the color sensor and the IR sensor to respectively capture multiple color images and multiple IR images by adopting multiple exposure conditions suitable for the imaging scene; adaptively select a combination of the color image and the IR image that can reveal details of the imaging scene; and fuse the selected color image and IR image to generate a scene image with details of the imaging scene.

A dual sensor imaging system and a calibration method thereof are provided. The dual sensor imaging system includes at least one color sensor, at least one infrared ray (IR) sensor, a storage device, and a processor. The processor is configured to load and execute a computer program stored in the storage device to: control the color sensor and the IR sensor to respectively capture multiple color images and multiple IR images of an imaging scene by adopting multiple capturing conditions; calculate multiple color image parameters of the color image captured under each capturing condition and multiple IR image parameters of the IR image captured under each capturing condition to be used to calculate a difference between a brightness of the color image and a brightness of the IR image; and determine an exposure setting suitable for the color sensor and the IR sensor according to the calculated difference.

Dual sensor imaging system and calibration method which includes a color sensor and an infrared ray sensor to perform image alignment and brightness matching

An image generating method and an electronic apparatus are provided. The method includes: determining whether at least one object in a plurality of first images to be captured will generate a blur to generate a determination result; determining a first amount of at least one second image in the plurality of first images and a second amount of at least one third image in the plurality of first images according to the determination result, wherein a first setting for capturing the second image is different from a second setting for capturing the third image; capturing the second image according to the first setting; capturing the third image according to the second setting; using the first amount of the second image and the second amount of the third image to perform an image superposition operation to generate an output image; and outputting the output image.

Image generating method and electronic apparatus

A multi-camera electronic device and a control method thereof are proposed. The method includes the following steps. At least one camera of the electronic device is used for scene detection to generate photographing analysis information. All the photographing analysis information is collected, and joint photographing information including a joint target is generated through a communication process among all the cameras. An individual photographing parameter of each camera is generated according to the joint photographing information. Each camera is controlled to capture an image of the scene by using its individual photographing parameter to respectively generate a corresponding output image.

Multi-camera electronic device and control method thereof

A method of multi-frame image noise reduction suitable for an image-capturing device includes following steps: obtaining a current frame and multiple reference frames; defining a mask and a target point in the mask; judging whether the target point pixel of the current frame is on an edge according to an edge map of the frame; when the pixel is on the edge, using the pixels in the reference frames on the edge to calculate a replacement result; when the target point pixel is not on the edge, using the pixels in the reference frames surrounding the target point to calculate a replacement result; after that, generating a pixel corresponding to the position of the target point in an output image according to the replacement result; further, moving the mask and going back to judge whether the pixel of the target point of the current frame is on the edge.

Method of multi-frame image noise reduction

An image processing method is provided and includes the following steps. A source image arranged in a Bayer pattern is captured. A first-order image process is performed on the source image to produce a first image in YCbCr format. A second-order image process is performed on the source image to produce a second image in YCbCr format. Then, a noise-reducing process is performed on the first image in YCbCr format to produce a noise-reduced image. A blending operation is performed on luminance image of the noise-reduced image and luminance image of the second image in YCbCr format, and thereafter a chrominance image is combined with the blended image to produce a processed image. A noise reducing degree of the noise-reduced image is higher than that of the second image in YCbCr format.

Image processing method

The present invention discloses a method of image denoising and method of generating motion vector data structure thereof. The method comprises: providing an image sequential capturing module to capture and to receive the plurality of images; generating a global motion vector based on the plurality of images in accordance with a first algorithm; reducing each image as reduced images; dividing each of the first reduced images into a plurality of first areas and generating a first local motion vector based on each of the first areas in accordance with a second algorithm, and via the similar way for generating a second local motion vector; finally, obtaining motion vector data in the plurality of images according to the global motion vector, each of the first local motion vectors and each of the second local motion vectors.

Method of image denoising and method of generating motion vector data structure thereof

An entered image is divided into a plurality of windows and it is determined, on a per-window basis, whether the image data within an applicable window is indicative of the color white, based upon the position of each window in the image and the continuity to its surrounding divided windows. A white balance method is performed based upon data of a window determined to be indicative of the color white. The present invention conducts a white balance process through the addition of determining the light source type weight and calculating the continuity of each divided window and its surrounding divided windows. In order the white balance process to accurately obtain the colors of an entered image even under the conditions of specific scenes with distinctive colors.

White balance method and apparatus thereof

The present invention discloses an image sharpness processing apparatus and an image sharpness processing method thereof. The apparatus comprises an image capturing module and a processing module. The image capturing module captures an image having a plurality of pixels. The processing module gains a characteristic value corresponding to each pixel by analyzing each pixel in the image. The processing module calculates a first sharpening compensation value and a second sharpening compensation value of each pixel by using a first sharpening algorithm and a second sharpening algorithm respectively, and determines a weight value of the first sharpening algorithm and the second sharpening algorithm by the characteristic value. The processing module calculates a third sharpening compensation value according to the first sharpening compensation value and the second sharpening compensation value, so as to adjust the sharpness of the image.

Image sharpness processing apparatus and image sharpness processing method

An automatic focusing method and device in a high-noise environment are used for determining a focusing distance between a digital imaging device and an object to be photographed. The automatic focusing method includes the steps of capturing M pre-photographed images at different object distances respectively; loading the pre-photographed images; superposing every N (N&#x3c;M) pre-photographed images to create (M&#x2212;N+1) composite images; redefining the object distances corresponding to the (M&#x2212;N+1) composite images; calculating high-frequency signals in the focusing regions of the (M&#x2212;N+1) composite images; determining an optimum focusing object distance based on the relation between the high-frequency signals and corresponding object distances; and adjusting an automatic focusing lens to the optimum focusing object distance and accomplishing focusing.

Automatic focusing method and device in high-noise environment

A method for analyzing object motion in multi frames adapted to an image capturing device is provided. Firstly, a plurality set of first sum of absolute difference (SAD) are obtained according to noise of the image capturing device under a plurality of light settings. Next, two frames are captured under a picturing light setting of the light settings. Then, a plurality of second SAD between the two frames are calculated. Afterwards, a plurality of object block within vein tracking of the object are found. Next, a local motion vector of each object block is respectively calculated according to the second SAD. Then, a first reliability of each object block is respectively calculated according to the second SAD and the set of the first SAD corresponding to the picturing light setting. Afterwards, the local motion vectors are estimated according to the first reliability to obtain a global motion vector.

Method for analyzing object motion in multi frames

A method for generating an all-in-focus image is provided. In the method, a plurality of frames including one source frame and several reference frames captured at different focus lengths are obtained. After performing a motion compensation procedure on the frames, for each pixel position belonging to an edge, a characteristic similarity between the source frame and each reference frame is calculated respectively to accordingly select a plurality of qualified reference frames among the reference frames. The method further includes determining a first type color space component of the pixel position within an all-in-focus image by an edge sharpness corresponding to the pixel position within each of the source frame and the qualified reference frames, and determining a second type color space component of the pixel position within the all-in-focus image by an color brightness corresponding to the pixel position within each of the source frame and the qualified reference frames.

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Taipei, Taiwan

Shih-Yuan Peng