#### DMCA

## Particle Swarm based Unsharp Masking

### Citations

4675 | A Computational Approach to Edge Detection.”
- Canny
- 1986
(Show Context)
Citation Context ...hich ultimately tends to reduce the blur metric. The blur metric,η, is computed from the width and amount of the edges in the image, obtained through edge detection algorithm. Since the canny operator=-=[19]-=- works good in terms of reduced false detection, edge localization, suppressing multiple edges, it is used to find the edges of an image. Canny edge detector, which is an optimal edge detector among o... |

374 |
Digital Image Processing.
- Pratt
- 1978
(Show Context)
Citation Context ...e application in remote sensing, medical imaging, surveillance, security and communication. The acquired images are subjected to storage, transmission and process to interpret the objects within them =-=[1]-=-. The visual interpretation of the image depends on the quality of the image. The contrast and fine details determine the visual quality of an image. However, most of the low cost imaging ∗Correspondi... |

106 |
A noreference perceptual blur metric,” in
- Marziliano, Dufaux, et al.
- 2002
(Show Context)
Citation Context ...n put forward to be used as fitness function to the PSO. 2.2.1 Fitness Function The blur metric, which measures blur present in an image, based on the analysis of the spread of the edges in the image =-=[18]-=-. Since blur metric is a no- reference measurement for edge sharpness, it can be used as self-evaluating objective function in the proposed framework to optimize the scaling factor, λ. The blur metric... |

63 | Study and comparison of various image edge detection techniques."
- Maini, HimanshuAggarwal
- 2009
(Show Context)
Citation Context ...cording to [16], Laplacian of Gaussian (LoG) filter outperforms the other gradient operators. However, the larger scale of variance of the Gaussian leads to the less accurate in the edge localization =-=[17]-=-. Laplacian mask is a second-order derivative, isotropic filter which is rotation invariant to the image. Since Laplacian operator highlights gray-level discontinuities in an image and deemphasizes re... |

14 |
Performance Evaluation of Edge Detection Techniques for Images in Spatial Domain”,
- Juneja, Sandhu
- 2009
(Show Context)
Citation Context ...pass filters like prewitt, sobel can be used to obtain gradient of the image. The high pass filter used for edge enhancement should be immune to noise and provide best edge localization. According to =-=[16]-=-, Laplacian of Gaussian (LoG) filter outperforms the other gradient operators. However, the larger scale of variance of the Gaussian leads to the less accurate in the edge localization [17]. Laplacian... |

12 | Selection Weighted Vector Directional Filters,
- Lukac, Smolka, et al.
- 2004
(Show Context)
Citation Context ...netic algorithm (GA), particle swarm optimization can play a role in optimizing user specified values to provide the good edge enhancement. The coefficients of weighted vector direction filter (WVDF) =-=[12]-=- are optimized using GA to enhance the contrast and detail enhancement [13]. It incorporates the mean absolute error (MAE), requires the original image, for GA optimization. In real time, obtaining th... |

11 |
Weighted median image sharpeners for the world wide web,”
- Fischer, Paredes, et al.
- 2002
(Show Context)
Citation Context ...r is proposed to smoothen, sharpen and outlier rejection [5]. Weighted median filter (WMF) has been experimented as a replacement for high-pass filters in the UM and also provides outlier suppression =-=[6]-=-. The extension of linear combination of polynomial terms in quadratic volterra(QV) filters [7] with WM, called quadratic weighted median filter (QWM) is derived to yield robust outlier rejection and ... |

11 |
A general framework for quadratic Volterra filters for edge enhancement
- Thurnhofer, Mitra
- 1996
(Show Context)
Citation Context ...been experimented as a replacement for high-pass filters in the UM and also provides outlier suppression [6]. The extension of linear combination of polynomial terms in quadratic volterra(QV) filters =-=[7]-=- with WM, called quadratic weighted median filter (QWM) is derived to yield robust outlier rejection and noise suppression [8]. Morphological filters are also used to detect the edges and sharpen them... |

7 |
Quadratic weighted median filters for edge enhancement of noisy images
- Aysal, Barner
- 2006
(Show Context)
Citation Context ... linear combination of polynomial terms in quadratic volterra(QV) filters [7] with WM, called quadratic weighted median filter (QWM) is derived to yield robust outlier rejection and noise suppression =-=[8]-=-. Morphological filters are also used to detect the edges and sharpen them [9]. The band-pass characteristics of bilateral filters are refined in band pass epsilon filter (BPEF) and used for edge enha... |

4 |
Edge-Detected Guided Morphological Filter for Image Sharpening
- Mahmoud, Marshall
(Show Context)
Citation Context ...with WM, called quadratic weighted median filter (QWM) is derived to yield robust outlier rejection and noise suppression [8]. Morphological filters are also used to detect the edges and sharpen them =-=[9]-=-. The band-pass characteristics of bilateral filters are refined in band pass epsilon filter (BPEF) and used for edge enhancement [10]. An adaptive linear filter based on neural network (NN) is introd... |

2 |
Piecewise Linear Model-Based Image Enhancement
- Russo
(Show Context)
Citation Context ...tant in low resolution image processing such as identification of people in closed-circuit television camera. Generally, the edge sharpening filters are classified into linear and non- linear filters =-=[3]-=-. A classical linear method for edge enhancement is simple unsharp masking (UM). A fraction of the high pass filtered image is added to the original data and the resulting effect produces edge enhance... |

2 |
filters: A class of rank-order-based filters for smoothing and sharpening
- Lum
- 1993
(Show Context)
Citation Context ...ed to provide better compromise between the image sharpening and noise attenuation. An order statistical filter, lower-upper-middle (LUM) filter is proposed to smoothen, sharpen and outlier rejection =-=[5]-=-. Weighted median filter (WMF) has been experimented as a replacement for high-pass filters in the UM and also provides outlier suppression [6]. The extension of linear combination of polynomial terms... |

2 |
Alaa Sheta, Aladdin Ayesh, Image Enhancement Using Particle Swarm Optimization
- Braik
- 2007
(Show Context)
Citation Context ...14 1.3828 0.1879 WMF 0.9150 1.3949 0.2102 QV 0.9114 1.3828 0.1879 QWM 0.8983 1.3956 1.6925 EDMOG 0.9204 1.352 0.1682 PSUM 0.9487 1.3584 0.1117 Table 7: Convergence rate of PSUM vs Existing methods in =-=[21]-=- for ’Cameraman’ Image Methods Convergence GA in [21] 32 PSO in [21] 28 Proposed PSUM 21 and PSO based methods. The computational complexity of the proposed PSUM relies on the velocity and position up... |

1 |
Noise Reduction and Edge Enhancement Based on
- Matsumoto, Hashimoto
- 2009
(Show Context)
Citation Context ...logical filters are also used to detect the edges and sharpen them [9]. The band-pass characteristics of bilateral filters are refined in band pass epsilon filter (BPEF) and used for edge enhancement =-=[10]-=-. An adaptive linear filter based on neural network (NN) is introduced to detect the artifacts, reduce them and enhance the edges [11]. It requires the enormous amount of dataset to train them so that... |

1 |
Adaptive Video Enhancement using Neural Network
- Lee, Park, et al.
- 2009
(Show Context)
Citation Context ... in band pass epsilon filter (BPEF) and used for edge enhancement [10]. An adaptive linear filter based on neural network (NN) is introduced to detect the artifacts, reduce them and enhance the edges =-=[11]-=-. It requires the enormous amount of dataset to train them so that the edge enhancement depends on the content of the training dataset. Most of the filters in literature consist of a lot of user-defin... |

1 |
Andrius Usinskas. A Study of Genetic Algorithms Applications for Image Enhancement and Segmentation
- Paulinas
(Show Context)
Citation Context ...zing user specified values to provide the good edge enhancement. The coefficients of weighted vector direction filter (WVDF) [12] are optimized using GA to enhance the contrast and detail enhancement =-=[13]-=-. It incorporates the mean absolute error (MAE), requires the original image, for GA optimization. In real time, obtaining the good quality reference image is impossible. Thus the independence of the ... |

1 |
Guru Revathi. A Particle Swarm Optimization Based Edge Preserving Impulse Noise Filter
- Roomi, Karuppi, et al.
(Show Context)
Citation Context ...quality reference image is impossible. Thus the independence of the edge sharpening technique with respect to the original image (No Reference) can make the enhancement process, self evolutionary. In =-=[14]-=-, a self-evolutionary Particle Swarm Optimization (PSO) technique is utilized for removing impulse noise. A contrast and detail enhancement algorithm based on optimizing this non-linear problem throug... |

1 |
Alaa Sheta, Aladdin Ayesh. Particle swarm optimisation enhancement approach for improving image quality
- Braik
(Show Context)
Citation Context ...le Swarm Optimization (PSO) technique is utilized for removing impulse noise. A contrast and detail enhancement algorithm based on optimizing this non-linear problem through PSO has been presented in =-=[15]-=-. The proposed self-evolutionary UM uses PSO to adapt the scaling factor to enhance edges. This performs better than the existing methods available in literature. The rest of the paper is organized as... |

1 |
Contrast Enhancement Technique based on Visual Significance
- Roomi, Kumar
- 1999
(Show Context)
Citation Context ...e efficiency of an edge enhancement technique can be determined. Following sections briefly describes these measures. 3.2.1 Focus Focus present in an image can be calculated with statistical measures =-=[20]-=-. Let an image be partitioned into nonoverlapping S segments amd each image is partitioned W windows. Let M(Wk) be mean of k th window and D(Wk) be mean absolute deviation of kth window then Horizonta... |