Image fusion is defined as the process of combining two or more different images into a new single image retaining important features from each image with extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. In Spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the c...

Image fusion is defined as the process of combining two or more different images into a new single image retaining important features from each image with extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. In Spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the c...

Wavelet packet transform stands out in the field of image fusion for its good frequency characteristics, and pulse coupled neural network (PCNN) has a unique advantage in image processing. To resolve the problem of multi-spectral remote sensing image fusion, in this paper, we put forward an algorithm combined the wavelet packet and PCNN based on HIS transform.The algorithm will be carried out a...

Image fusion is defined as the process of combining tw o or more different images into a new single image retaining important features from each image w ith extended information content. There are two approaches to image fusion, namely Spatial Fusion and Transform fusion. In Spatial fusion, the pixel values from the source images are directly summed up and taken average to form the pixel of the...

The main objective of this paper is to study the composition continuous Kontorovich-Lebedev wavelet transform (KL-wavelet transform) and wave packet (WPT) based on (KL-transform). Estimates for KL-wavelet are obtained, Plancherel?s relation WPT-transform derived. Reconstruction formula WPT associated KL-transform also deduced at end Calderon?s related using its convolution property obtained.

Arbitrary-shape wavelet packet transform (ASWPT) is presented as an adjustment of the traditional quad-tree wavelet packet transform. The group normalization (GN) and softer logic masking (SLM) techniques are introduced for image restoration with optimal visual result and high PSNR.