[go: up one dir, main page]

Salekin et al., 2018 - Google Patents

Image De-Noising Through Symmetric, Bell-Shaped, and Centered Weighted Median Filters Based Subband Decomposition

Salekin et al., 2018

Document ID
11981570561704326494
Author
Salekin S
Agaian S
Jahan I
Sajal S
Publication year
Publication venue
2018 IEEE International Conference on Electro/Information Technology (EIT)

External Links

Snippet

Here, a novel image denoising algorithm that eliminates different type of noise from an image using median filter based subband decomposition. The benefit of sub-band decomposition using median transform over the wavelet decomposition method is that the …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/001Image restoration
    • G06T5/002Denoising; Smoothing
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/14Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G06F17/141Discrete Fourier transforms
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20048Transform domain processing
    • G06T2207/20064Wavelet transform [DWT]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20048Transform domain processing
    • G06T2207/20056Discrete and fast Fourier transform, [DFT, FFT]
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • G06F17/14Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G06F17/147Discrete orthonormal transforms, e.g. discrete cosine transform, discrete sine transform, and variations therefrom, e.g. modified discrete cosine transform, integer transforms approximating the discrete cosine transform
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/20Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image by the use of local operators

Similar Documents

Publication Publication Date Title
Easley et al. Sparse directional image representations using the discrete shearlet transform
Strela et al. Image denoising using a local Gaussian scale mixture model in the wavelet domain
US7260272B2 (en) Method and apparatus for noise reduction using discrete wavelet transform
Rabbani Image denoising in steerable pyramid domain based on a local Laplace prior
KR20190024636A (en) Method and apparatus for reconstructing image based on neural network
CN113204051A (en) Low-rank tensor seismic data denoising method based on variational modal decomposition
Khare et al. Multilevel adaptive thresholding and shrinkage technique for denoising using Daubechies complex wavelet transform
Zha et al. Noise reduction in interferograms using the wavelet packet transform and wiener filtering
Portilla et al. Image denoising via adjustment of wavelet coefficient magnitude correlation
Vimala et al. Noise reduction based on double density discrete wavelet transform
Chan et al. Wavelets for sensing technologies
Prakash et al. Medical image denoising based on soft thresholding using biorthogonal multiscale wavelet transform
Rosiles et al. Image denoising using directional filter banks
Gnanadurai et al. Image de-noising using double density wavelet transform based adaptive thresholding technique
Salekin et al. Image De-Noising Through Symmetric, Bell-Shaped, and Centered Weighted Median Filters Based Subband Decomposition
CN114331853A (en) Single image restoration iteration framework based on target vector updating module
Kaur et al. A survey on implementation of discrete wavelet transform for image denoising
Alwan Color image denoising using stationary wavelet transform and adaptive wiener filter
Adeyemi et al. Sparse representations of images using overcomplete complex wavelets
Narayan et al. A comparative analysis for Haar wavelet efficiency to remove Gaussian and Speckle noise from image
Singh et al. Analysis of Multispectral Image Using Discrete Wavelet Transform
Gupta et al. Removal of Gaussian noise from stationary image using shift invariant wavelet transform
Guangmin et al. Image denoising with optimized subband threshold
Arivazhagan et al. A new hybrid image restoration method based on fusion of spatial and transform domain methods
Shi et al. Image sharpening via image denoising in the complex wavelet domain