The present invention generally relates to compression, and, more particularly, to preprocessing image data before compression to reduce the presence of noise in an image, whether a still image or a sequence of images such as in a video.
Image data is typically large in size. This is especially so if the image data represents video. As such, and as known in the art, it is preferable to compress the image data before transmission, or even storage, of the image data. In this regard, there are numerous techniques for compressing image data that to one degree or another provide some level of fidelity to the original image data.
However, when compressing image data, the image data may include noise that can adversely affect the compression efficiency since compression algorithms generally cannot distinguish noise from desired detail in the image. In other words, the size of the compressed image data may be larger than is necessary due to the presence of noise in the image data. For example, if an image is first recorded on a video cassette recorder (VCR), the recorded image data—upon playback—may now include noise. As a result, use of the VCR as a source of the image data for streaming across the Internet may, even with compression, require the use of more bandwidth than would be necessary if the noise were not present in the image data to begin with.
As such, if the image data includes noise it is known to filter the image data to first attempt to remove, or reduce, any noise before compression of the image data. Typically, one of a number of known filter techniques is applied to the image data and the filtered image data is previewed to examine the affect on the fidelity of the image. Filter settings are made by viewing the filtered image and adjusting the filter controls in an attempt to find a compromise between reduced noise and blurring of image details. Too much filtering may blur the image, too little filtering will not remove enough of the noise in the image data to improve the compression efficiency. Unfortunately, it is especially difficult to remove low-level noise that is difficult, or impossible, to see in the image but which still reduces compression efficiency. This difficulty is compounded with video, in which the image data is constantly changing.