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In this work a new image sharpening technique based on multiscale analysis and wavelet fusion is presented. The proposed technique is suitable for visibility optimization of biomedical images obtained from MRI sensors. The proposed approach combines, with a wavelet based fusion algorithm, the sharpening results accrued from a number of independent image sharpening techniques. Initially, the input image is preprocessed by a denoising filter based on a complex Two Dimensional Dual-Tree Discrete Wavelet Transform. Then, the denoised image is passed through a cluster of five sharpening filters and subsequently, the final image is obtained with the help of a wavelet fusion technique. The main novelty of the proposed technique lies on using only one input image for sharpening and that the fusion is performed on images extracted in different frequency bands. This technique could be used as a preprocessing step in many applications. In this paper we focus on the application of the proposed technique in brain MR images. Specific image sharpening and quality indices are employed for the quantitative assessment of the proposed technique.

A New Sharpening Technique for Medical Images using Wavelets and Image Fusion