Abstract: A disclosed computer-implemented method may include receiving a media item for encoding via a content optimized encoding algorithm. The method may also include determining, in accordance with the content optimized encoding algorithm, an overall error model for the media item. The overall error model may include (1) a rate-distortion model for the media item, and (2) a downsampling-distortion model for the media item. The method may also include determining, based on the overall error model, a bitrate cost associated with streaming of the media item within a bitrate lane. The method may further include adjusting the overall error model based on the bitrate cost associated with streaming of the media item within the bitrate lane and encoding the media item for streaming within the bitrate lane based on the adjusted overall error model.

Abstract: The invention pertains to an adaptive scaling technique. A look-up table of optimized filter coefficients is used to configure a multi-tap filter when scaling a video image. The look-up table reflects the scaling between standardized video source (input) resolutions and video display (output) resolutions. When an actual scaling factor does not correspond to an optimized operating point, a device driver determines which two scaling factors reflected in the look-up table are closest to the actual scaling factor. A set of interpolated filter coefficients for the multi-tap filter is then generated from the optimized filter coefficients associated with the two closest scaling factors. One advantage of the disclosed technique is that scaling operations are performed using filter coefficients interpolated from filter coefficients optimized for two similar scaling operations. Thus, the technique provides more precise filtering relative to prior art designs, resulting in higher-quality scaled video images.

Abstract: The image reconstruction method generates higher quality reconstructed images from compression of a bi-level image. The method includes thresholding to force pixels of the starting image to be closer to bi-level to generate a threshold image. The method transforms the threshold image to generate transform coefficients representing the decomposition of the threshold image. The method selectively clamps the transform coefficients into quantization bins defined by compression of the bi-level image. The selective clamping generates modified coefficients corresponding to the higher quality reconstructed image. The method also includes applying an inverse-transform on the modified coefficients to generate higher quality reconstructed image. The starting image and the reconstructed image can be compared to determine the degree of improvement obtained with the method. The method can be repeated iteratively to obtain an image that more closely represents the original image than does the original lower-quality image.