Lossless video coding is useful in applications where no loss of information or visual quality is tolerable. In embedded to lossless coding an encoded video stream can be decoded into any bit rate up to the lossless bit rate, which is quite useful in numerous applications. In this paper, the research we present is based on lossless video coding, which uses motion compensated prediction to eliminate temporal redundancy. We specifically address the problem of embedded to lossless coding of the motion compensated prediction residuals. Since the statistical properties of the residuals are different from still images, the best wavelet bases for still images do not perform well for residuals. Since residuals contain a higher portion of high frequency information in high motion regions, a fixed transform for the entire frame is not very efficient. We introduce a spatially adaptive wavelet transform method, which takes the local frame statistics into account before choosing the wavelet base. This transform technique provided the best performance for most of the test frames.
Three dimensional (3-D) images have recently received wide attention in applications involving medical treatment. Most current 3-D imaging methods focus on the internal organs of the body. However, several medical image applications such as plastic surgery, body deformities, rehabilitation, dental surgery and orthodontics, make use of the surface contours of the body. Several techniques are currently available for producing 3-D images of the body surface and most of the systems which implement these techniques are expensive, requiring complex equipment with highly trained operators. The research involves the development of a simple, low cost and non-invasive contour capturing method for facial surfaces. This is achieved using the structured light technique, employing a standard commercial slide projector, CCD camera and a frame-grabber card linked to a PC. Structured light has already been used for many applications, but only to a limited extent in the clinical environment. All current implementations involve extensive manual intervention by highly skilled operators and this has proven to be a serious hindrance to clinical acceptance of 3-D imaging. A primary objective of this work is to minimize the amount of manual intervention required, so that the system can be used by clinicians who do not have specialist training in the use of this equipment. The eventual aim is to provide a software assisted surgical procedure, which by merging the facial data, allows the manipulation of soft tissue and gives the facility to predict and monitor post-surgical appearance. The research focuses on how the images are obtained using the structured light optic system and the subsequent image processing of data to give a realistic 3-D image.
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