This paper presents a new image data fusion scheme by combining median filtering with self-organizing feature map (SOFM) neural networks. The scheme consists of three steps: (1) pre-processing of the images, where weighted median filtering removes part of the noise components corrupting the image, (2) pixel clustering for each image using self-organizing feature map neural networks, and (3) fusion of the image, (2) pixel clustering for each image using self-organizing feature map neural networks, and (3) fusion of the images obtained in Step (2), which suppresses the residual noise components and thus further improves the image qeuality. It proves that such a three-step com bination offers an impressive effectiveness and performance improvement, which is confirmend by simulations involving three image sensors (each of which has a different noise structure).

The classified side-match vector quantizer, CSMVQ, has already been presented for low-bit-rate image en-coding. It exploits a block classifier to decide which class the input vector belongs to using the variances of the upper and left codewords. However, this block classifier doesn't take the variance of the cnrrcnt input vector itsclf into accounl, This let-ter presents a new CSMVQ in which a two-level block classifier is used to classify input vectors and two diffrent master code-books are used for generating the state codebook according to the variance of the input vcctor. Experimental results prove the cffectivcness of the proposed CSMVQ.

The fast codeword search algorithm based on the mean pyramids of codewords is currently used in image coding applications. A more efficient algorithm is presented for fast codeword searching which is based on the use of mean-variance pyramids of codewords. Experimental results confirm the effectiveness of the proposed method.

A new fast codeword search algorithm for imagc vcctor quantisation (VQ) is introduced. This algorithm performs a fast codeword search in the Hadamard transform (HT) domain using the partial distance search (PDS) technique, Experimental results show that the algorithm needs only 2-3% of the distortion calculations of the exhaustive search method.

A digital image watermarking technique based on vector quantisation (VQ) is presented. This technique uses codeword indices to carry the watermark information. The technique is secret and efficient, and the watermarked image is robust to VQ compression with the same codebook. The simulation results prove the effectiveness of this technique.