Abstract: A Method for processing RGBIR (Red Green Blue Infrared) multi-frame HDR (High Dynamic Range) with luma includes capturing a plurality of RGBIR raw images with different exposure times by at least one camera, generating a plurality of luma images using a color filter array luma (CFAL) filter according to the plurality of RGBIR raw images, performing IR color correction to generate a plurality of corrected RGBIR raw images according to the RGBIR raw images, performing HDR fusion to generate a HDR RGBIR raw image according to the plurality of luma images and the plurality of corrected RGBIR raw images, generating gradients according to the HDR RGBIR raw image and the plurality of luma images, and performing interpolation to generate a result image according to at least the gradients and the HDR RGBIR raw image.

Abstract: An image interpolation method comprises applying a filter to an RGBIR image to generate a LUMA image; calculating two gradients according to the LUMA image; and interpolating a missing pixel between two pixels in the RGBIR image according to the two gradients. Wherein each gradient corresponding to two LUMA pixels in the LUMA image. An image fusion method comprises applying a filter to an RGBIR image to generate a LUMA image; obtaining an R-image, a G-image, a B-image and an IR image according to the RGBIR image; and generating a fusion image according to the R-image, G-image, B-image, the IR image and the LUMA image.

Abstract: Firstly, a measurement space is defined with a plurality of voxels. When the object is located within the measurement space, at least a depth map of the object is generated by photographing the object from at least a viewpoint. View direction and coordinates of the at least a viewpoint are also obtained. A plurality of redundant voxels, which are not belong to the object, are eliminated from the measurement space according to the at least a map, the view direction and the coordinates of the at least a viewpoint. The volume and/or the dimension of the object is calculated based on remaining voxels of the measurement space after the redundant voxels are eliminated from the measurement space.

Abstract: A face detecting method and a face detecting system are provided. The face detecting method includes the following steps: At least one original image block is received. The original image block is transformed by a transforming unit to obtain a plurality of different transformed image blocks. Whether each of the transformed image blocks contains a face is detected by a detecting unit according to only one identical face database and a detecting result value is outputted accordingly. The transformed image blocks are detected by a plurality of parallel processing cores. Whether a maximum of the detecting result values is larger than a threshold value is determined by a determiner. If the maximum of the detecting result values is larger than the threshold value, then the determiner deems that the original image block contains a face.

Abstract: An image processing method and a device for redeye correction are provided. In the method, a face region of a pending image is received and detected. At least one region of interest (ROI) is set in the face region. The ROI is segmented according to a color model so as to produce a plurality of candidate regions. Each of the candidate regions is filtered separately according to a candidate region filtering method. It is determined whether a color candidate region is produced after filtering. If yes, luminance values of a plurality of pixels in the ROI are calculated by a contrast mask. The ROI is segmented by using a calculated luminance distribution so as to produce a high contrast candidate region. An overlapped portion between the color and the high contrast candidate regions is taken as a redeye region, and the redeye region is corrected to produce a corrected image.