Ma et al., 2023 - Google Patents
An overview of digital image analog noise removal based on traditional filteringMa et al., 2023
- Document ID
- 5597156884103210027
- Author
- Ma Y
- Zhang T
- Lv X
- Publication year
- Publication venue
- International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2023)
External Links
Snippet
Due to interference in the transmission of external equipment, images can suffer from varying noise concentrations. As an immediate and practical step to reduce the impact of noise on an image and to improve its quality and visual presentation, filtering is the best …
Classifications
-
- 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
- G06T2207/20182—Noise reduction or smoothing in the temporal domain; Spatio-temporal filtering
-
- 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
- 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
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20048—Transform domain processing
- G06T2207/20064—Wavelet transform [DWT]
-
- 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
- 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
- G06T2207/20112—Image segmentation details
-
- 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
- G06T5/005—Retouching; Inpainting; Scratch removal
-
- 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
- G06T5/20—Image enhancement or restoration, e.g. from bit-mapped to bit-mapped creating a similar image by the use of local operators
-
- 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
- G06T2207/10016—Video; Image sequence
-
- 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
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
- G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
- G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
- G06K9/46—Extraction of features or characteristics of the image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T11/00—2D [Two Dimensional] image generation
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Bhutada et al. | Edge preserved image enhancement using adaptive fusion of images denoised by wavelet and curvelet transform | |
Li et al. | Multifocus image fusion based on redundant wavelet transform | |
Bhateja et al. | A non-local means filtering algorithm for restoration of Rician distributed MRI | |
CN112150386B (en) | SAR image speckle non-local average inhibition method based on contrast mean value | |
Cheon et al. | A modified steering kernel filter for AWGN removal based on kernel similarity | |
Wang et al. | An efficient remote sensing image denoising method in extended discrete shearlet domain | |
Panigrahi et al. | Joint bilateral filter for signal recovery from phase preserved curvelet coefficients for image denoising | |
Chakraborty et al. | A multi-level method noise based image denoising using convolution neural network | |
Ma et al. | An overview of digital image analog noise removal based on traditional filtering | |
Goyal et al. | Review paper on various filtering techniques and future scope to apply these on TEM images | |
Biswas et al. | A model of noise reduction using Gabor Kuwahara filter | |
Huang et al. | Fast color-guided depth denoising for RGB-D images by graph filtering | |
Budhiraja et al. | Infrared and visible image fusion based on sparse representation and spatial frequency in DTCWT domain | |
Razman et al. | Filtering technique in ultrasound for kidney, liver and pancreas image using Matlab | |
Zhu et al. | Experimental study on image filtering algorithm | |
Sukhatme et al. | Independent component analysis based denoising of magnetic resonance images | |
Nair et al. | Denoising of sar images using maximum likelihood estimation | |
Annam et al. | Correlative analysis of denoising methods in spectral images embedded with different noises | |
Mamatha et al. | Performance analysis of various filters for De-noising of Handwritten Kannada documents | |
Moreno et al. | Evaluation of sharpness measures and proposal of a stop criterion for reverse diffusion in the context of image deblurring | |
Ashwini et al. | Noise2split—single image denoising via single channeled patch-based learning | |
Gupta et al. | A Review on Image Denoising | |
Ehsaeyan | A new shearlet hybrid method for image denoising | |
ZHOU et al. | Research on the Improved BM3D Denoising Algorithm for Remote Sensing Images Based on Context Aggregation Network | |
Kumar et al. | Two Stage Image Restoration based on Histogram Equalization and Edge Computation for Image |