Ten lectures on wavelets
Wavelets and filter banks: theory and design
IEEE Transactions on Signal Processing
Data compression and harmonic analysis
IEEE Transactions on Information Theory
The JPEG2000 still image coding system: an overview
IEEE Transactions on Consumer Electronics
High performance scalable image compression with EBCOT
IEEE Transactions on Image Processing
The curvelet transform for image denoising
IEEE Transactions on Image Processing
The finite ridgelet transform for image representation
IEEE Transactions on Image Processing
Sparse geometric image representations with bandelets
IEEE Transactions on Image Processing
The contourlet transform: an efficient directional multiresolution image representation
IEEE Transactions on Image Processing
Interactive content based image retrieval using ripplet transform and fuzzy relevance feedback
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
Hi-index | 0.00 |
Efficient representation of images usually leads to improvements in storage efficiency, computational complexity and performance of image processing algorithms. Efficient representation of images can be achieved by transforms. However, conventional transforms such as Fourier transform and wavelet transform suffer from discontinuities such as edges in images. To address this problem, we propose a new transform called ripplet transform. The ripplet transform is a higher dimensional generalization of the curvelet transform, designed to represent images or two-dimensional signals at different scales and different directions. Specifically, the ripplet transform allows arbitrary support c and degree d while the curvelet transform is just a special case of the ripplet transform (Type I) with c=1 and d=2. Our experimental results demonstrate that the ripplet transform can provide efficient representation of edges in images. The ripplet transform holds great potential for image processing such as image restoration, image denoising and image compression.