The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Sparse representation using the over-complete dictionary makes that decomposition coefficients are more sparse, and can reflect the inherent characteristics and structure of signals. A novel fusion method based on IHS transform and sparse representation for multi-spectral image and panchromatic image is proposed in this paper. Firstly, the IHS transform is applied to multi-spectral image. Then, the...
This article compares four different alternative image representations in the context of a structure-based change detection. The framework is taken from the already published Curvelet-based change detection approach. Only the transform step is modified by inserting three additional transforms: the Laplacian pyramid, the Wavelet and the Surfacelet transform. The results of the change detection are...
Representation of 3D shape is an important property of 3D object retrieval. Representing 3D shape features in a suitable format that includes important geometrical characteristic is not trivial. Existing current feature vector methods represent 3D shape function using a sphere. However, it can not fully characterize the approximation of 3D shape. Generally 3D shapes are irregular in nature. Ellipsoidal...
Human body pose modelling system is directly influenced by the image features used in the system, its model representation and also its application. This paper presents silhouette, edge and colour extraction methodology for detecting the human body parts in image sequences. Silhouette is used as input for head and torso pose estimation. Meanwhile, edge and colour are used respectively as input for...
Magnetic resonance (MR) brain image has been accepted as the reference image in the clinical research. The goal of MR brain image segmentation is to accurately identify the principal tissue structures in the image volumes. In this paper, the segmentation algorithm based on SOM (self-organizing map) neural network with compression pre-processing by wavelet transform is presented. The compression idea...
This paper presents an adaptive sparse representation scheme for the remote sensing image, the geometric structure of which is more complex than that of natural image. The presented scheme includes two main stages which are wavelet transform and adaptive directional filter which is designed based on a binary tree. The construction of the binary tree depends on the image geometric information in frequency...
Threshold selection is the critical issue in image denoising. This paper deal with a new multiscale directional representation called the shearlet transform that has shown to represent specific classes of images with distributed discontinuities optimally. Techniques based on this transform for denoising using an efficient adaptive shrinkage threshold are presented. The shearlet transform not only...
In this work, a nonlinear geometric transform, called peak transform (PT), has been introduced for efficient image representation and coding. The proposed PT is able to convert high-frequency signals into low-frequency ones, making them much easier to be compressed. In combination with wavelet transform and subband decomposition, the PT is able to significantly reduce signal energy in high-frequency...
Among transform-based image compression methods, the sparsity of transform coefficients is very important for compression performance. To overcome the insufficiency of commonly used DCT and wavelet transform, we apply the theory of adaptive over-complete sparse representation to the filed of facial image compression. By using a novel dictionary design algorithm called K-LMS, which recently proposed...
This paper proposes a novel hybrid image denoising method based on wavelet transform and sparse and redundant representations model which is called signal-scale wavelet K-SVD algorithm (SWK-SVD). In wavelet domain, mutiscale features of images and sparse prior of wavelet coefficients are achieved in a natural way. This gives us the motivation to build sparse representations in wavelet domain. Using...
Curvelet transform is one of the recently developed multiscale transform, which can well deal with the singularity of line and provides optimally sparse representation of images with edges. But now the image denoising based on curvelet transform is almost used the Monte Carlo threshold, it is not used the feature of imagespsila curvelet coefficients effectively, so the best result can not be reached...
Contourlet transform provides a flexible multiresolution, local and directional image expansion and a sparse representation for two dimensional piecewise smooth signal resembling images. It overcomes the weakness of wavelet transform in dealing with high dimensional signals. In this paper, the theory of contourlet transform is introduced and a new approach of facial expression recognition based on...
Wavelet transforms have been successfully used in many scientific fields such as image denoising. Ridgelets is a new system of representations, which deals effectively with line singularities in 2D. However, the discrete version of the ridgelet transform would result in either redundancy or non-reconstruction. In this paper, a pseudo ridgelet transform is developed to overcome this weakness. Since...
The protection of intellectual property rights became recently a pressing need especially with the rapid growth of transmission techniques. In this paper, we present as a copyright protection method, a blind video watermarking technique based on video scene segmentation and 3D wavelet transform. First, a gray scale image as copyright sign is decomposed with different resolution and embedded in the...
Contourlet is a new effective signal representation tool in many image applications. In this paper, a contourlet-based image denoising algorithm using adaptive windows which utilizes both the captured directional information by the contourlet transform and the intrinsic geometric structure information of the image is proposed. The adaptive window in each of the contourlet subband is first fixed by...
Multiresolution (MR) representations have been very successful in image encoding, due to both their algorithmic performance and coding efficiency. However these transforms are fixed, suggesting that coding efficiency could be further improved if a multiresolution code could be adapted to a specific signal class. Among adaptive coding methods, independent component analysis (ICA) provides the best...
As a directional multiresolution image representation, the contourlet transform can efficiently capture curved and oriented geometrical structures in images. However, the contourlet transform has the drawback of a 4/3 redundancy in its oversampling ratio. Recently, Zhang and Moloney have developed a nonredundant version of the contourlet transform, called the nonredundant contourlet transform (NRCT)...
Multi-scale curvelet transform is a new extension to wavelet transform in two dimensions. The directionality feature of curvelet transform makes it a good choice for representation of curves and edges in the image. The second generation curvelet transform theory makes it understood and implemented more easily. In this paper, a novel algorithm is proposed to improve compression performance by using...
Edge of image is one of the most fundamental and significant features. Edge detection is always one of the classical studying projects of computer vision and image processing field. It is the first step of image analysis and understanding. The purpose of edge detection is to discover the information about the shapes and the reflectance or transmittance in an image. It is one of the fundamental steps...
In content-based image retrieval, the method based on salient points detection is one of the most active research areas for it can represent the local properties of the image. This paper proposes an improved salient points detector based on wavelet transform which can extract salient points more exactly. Then, an annular segmentation algorithm based on salient points distribution is designed, which...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.