Nothing Special   »   [go: up one dir, main page]

Singh et al., 2016 - Google Patents

A comparative performance analysis of DCT-based and Zernike moments-based image up-sampling techniques

Singh et al., 2016

Document ID
14439848694412048597
Author
Singh C
Aggarwal A
Publication year
Publication venue
Optik

External Links

Snippet

The DCT-based image up-sampling methods are very effective and simple for image super- resolution in the DCT domain. We compare the performance of three major DCT-based image interpolation methods and propose Zernike moments (ZMs)-based up-sampling …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/40—Scaling the whole image or part thereof
    • G06T3/4084—Transform-based scaling, e.g. FFT domain scaling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/40—Scaling the whole image or part thereof
    • G06T3/4053—Super resolution, i.e. output image resolution higher than sensor resolution
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20048—Transform domain processing
    • G06T2207/20056—Discrete and fast Fourier transform, [DFT, FFT]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T3/00—Geometric image transformation in the plane of the image, e.g. from bit-mapped to bit-mapped creating a different image
    • G06T3/40—Scaling the whole image or part thereof
    • G06T3/4007—Interpolation-based scaling, e.g. bilinear interpolation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20172—Image enhancement details
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10024—Color image
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/001—Image restoration
    • G06T5/002—Denoising; Smoothing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image
    • G06T5/001—Image restoration
    • G06T5/003—Deblurring; Sharpening
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20016—Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T11/00—2D [Two Dimensional] image generation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G06T1/0021—Image watermarking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis

Similar Documents

Publication Publication Date Title
Zhao et al. Multi-focus image fusion based on the neighbor distance
Anbarjafari et al. Image super resolution based on interpolation of wavelet domain high frequency subbands and the spatial domain input image
Prashanth et al. Image scaling comparison using universal image quality index
Wei et al. FRESH—FRI-based single-image super-resolution algorithm
US20160048947A1 (en) Upsampling and signal enhancement
Sajjad et al. Multi-kernel based adaptive interpolation for image super-resolution
Hung et al. Novel DCT-Based Image Up-Sampling Using Learning-Based Adaptive ${k} $-NN MMSE Estimation
Vishnukumar et al. Single image super-resolution based on compressive sensing and improved TV minimization sparse recovery
Kato et al. Double sparsity for multi-frame super resolution
Nandi et al. Sparse representation based multi‐frame image super‐resolution reconstruction using adaptive weighted features
Barzigar et al. A video super-resolution framework using SCoBeP
Vishnukumar et al. Edge preserving single image super-resolution with improved visual quality
Singh et al. A comparative performance analysis of DCT-based and Zernike moments-based image up-sampling techniques
Karimi et al. A survey on super-resolution methods for image reconstruction
Lama et al. Image interpolation for high-resolution display based on the complex dual-tree wavelet transform and hidden Markov model
Muhammad et al. Image noise reduction based on block matching in wavelet frame domain
Saito et al. Super-resolution interpolation with a quasi blur-hypothesis
Choi et al. Color image interpolation in the DCT domain using a wavelet-based differential value
Wu et al. Wavelet Domain Multidictionary Learning for Single Image Super‐Resolution
Singh et al. A content adaptive method of de-blocking and super-resolution of compressed images
Lee et al. Weighted DCT-IF for Image up Scaling
Zhang et al. Single depth map super-resolution via joint non-local self-similarity modeling and local multi-directional gradient-guided regularization
Callicó et al. Low-cost super-resolution algorithms implementation over a HW/SW video compression platform
Acharya et al. Composite high frequency predictive scheme for efficient 2-D up-scaling performance
Acharya et al. Efficient fuzzy composite predictive scheme for effectual 2-D up-sampling of images for multimedia applications