Abstract: A method of assembly calibration for a multi-camera system is disclosed. The method comprises receiving at least two images respectively captured by at least two cameras in different angle of views, performing image transformation for aligning the received images which is optional, performing image motion estimation on an overlapping region of the images, for obtaining correspondence between the images with a plurality of motion vectors, wherein the plurality of motion vectors is used for indicating geometry relations between the images, performing dominant vector calculation according to the plurality of motion vectors, to obtain a dominant motion vector in region of interest (ROI) of the overlapping region, and calculating calibration parameters according to the obtained dominant motion vector, performing image correction according to the calibration parameters, to obtain a correct panoramic image covering the whole interested areas.

Abstract: A method of adaptive image stitching for an image stitching device is disclosed. The method comprises receiving at least two images respectively captured by at least two cameras in different angle of views, from the at least two cameras, performing image motion estimation on an overlapping region of the two images, to obtain correspondence between two images with a plurality of motion vectors, wherein the plurality of motion vectors is used for indicating a geometry relation between the two images, performing dominant vector calculation according to the plurality of motion vectors of the image motion estimation, for obtaining a dominant motion vector in region of interest (ROI) of the overlapping region, and stitching the two images into a single seamless image with a stitching radius calculated according to the dominant motion vector.

Abstract: A camera array system includes an image sensor device, a hybrid color filter array disposed above the image sensor device, and a lens array disposed above the hybrid color filter array. The hybrid color filter array includes plural kinds of monochromatic color filters and at least one mosaic filter; and the lens array includes a number of optic lenses. The at least one mosaic filter is utilized to perform stereo matching in order to estimate depth information.

Abstract: The present invention is directed to a rate-distortion optimized (RDO) transform and quantization system. A frame classification unit classifies an input frame as either a key frame or a non-key frame. A rate model update unit generates at least one model parameter of a rate model according to a transform coefficient and a bitrate resulted from an encoded key frame. An RDO transform and quantization unit processes the input frame, thereby generating a quantized transform coefficient according to the model parameter. A frame buffer is used to store a previous frame, according to which the bitrate is estimated.

Abstract: A camera array system includes an image sensor device, a hybrid color filter array disposed above the image sensor device, and a lens array disposed above the hybrid color filter array. The hybrid color filter array includes plural kinds of monochromatic color filters and at least one mosaic filter; and the lens array includes a number of optic lenses. The at least one mosaic filter is utilized to perform stereo matching in order to estimate depth information.

Abstract: A rate control method of perceptual-based rate-distortion (R-D) optimized bit allocation is disclosed. An input frame is firstly determined as a key frame or non-key frame. A key frame is additionally encoded to generate rate-distortion (R-D) points. The R-D model of each basic unit (BU) is updated, followed by perceptual-based bit allocation, thereby generating a target bit rate. A quantization parameter (QP) is computed according to the target bit rate, and the current BU is encoded according to the QP. A rate-quantization (R-Q) model is updated if not all BUs have been encoded.

Abstract: The present invention is directed to a rate-distortion optimized (RDO) transform and quantization system. A frame classification unit classifies an input frame as either a key frame or a non-key frame. A rate model update unit generates at least one model parameter of a rate model according to a transform coefficient and a bitrate resulted from an encoded key frame. An RDO transform and quantization unit processes the input frame, thereby generating a quantized transform coefficient according to the model parameter. A frame buffer is used to store a previous frame, according to which the bitrate is estimated.

Abstract: A rate control method of perceptual-based rate-distortion (R-D) optimized bit allocation is disclosed. An input frame is firstly determined as a key frame or non-key frame. A key frame is additionally encoded to generate rate-distortion (R-D) points. The R-D model of each basic unit (BU) is updated, followed by perceptual-based bit allocation, thereby generating a target bit rate. A quantization parameter (QP) is computed according to the target bit rate, and the current BU is encoded according to the QP. A rate-quantization (R-Q) model is updated if not all BUs have been encoded.