Preprocessing in Hardware
 The typical 3D noise reduction methods used in most products compare images in sequence over a predetermined period of time, blending the images between fields or frames. The simplified theory is that by blending data over time, you can reduce the overall noise content of the resulting image. This is used in the film industry to remove film grain from blue or green screen shots. Successive samples of the same blue or green screen scene are blended together which will effectively cancel out the noise found in any individual frame. The problem with typical noise reduction algorithms is that if the scene contains any motion, you will get a motion blur (trails) artifact in the processed frame. One answer to this is to limit the blending process to a specific range of frames or to restart the process every few frames, but this only partially solves the issue. This is very visible in the noise reduction found in some software codecs. Every few frames the noise will suddenly appear only to disappear several frames later; then the process starts over again.
The DRC-Stream hardware uses a very advanced form of temporal noise processing called motion adaptive 3D noise reduction. Motion adaptive 3D noise reduction combines the information in multiple frames of video on a pixel by pixel basis to decide how much processing is applied to each pixel in the final frame. Because each pixel is calculated individually, the result is more precise noise reduction with less motion blurring artifacts than would otherwise be normally possible. With troublesome footage, this can make the difference between barely viewable video and a high quality result. Check out the videos in our Example Clips section for samples demonstrating the advantage of motion adaptive 3D noise reduction.
Hardware-Based Filtering and Scaling
Another important processing step is linear filtering, which results in a smoother image that is ultimately easier for the codec to compress than one that is not properly filtered. If content requires less aggressive compression to achieve the same bandwidth, you will get an improvement in overall image quality. Digital Rapids encoding systems calculate what should be the optimal linear filtering based on the target resolution. This can be manually overridden for an even smoother image, with separate settings for vertical and horizontal filtering for maximum control – an advantage over competing systems that provide either no filtering, or global filtering without individual optimization.
Image scaling also contributes to the quality of the resulting compressed output. In systems which rely on the software codec to perform the scaling the entire full resolution data must be passed across the bus (potentially creating a bottleneck if encoding from multiple discrete input sources simultaneously), the scaling process consumes some CPU resources, and the quality of the image scaling may vary between codecs. The DRC-Stream hardware features very high quality image scaling, producing consistently outstanding quality without impacting performance.
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