We present Gibbs–Markov random field (GMRF) models as a powerful and robust descriptor of spatial information in typical remote-sensing image data. This class of stochastic image models provides an intuitive description of the image data using parameters of an energy function. For the selection among several nested models and the fit of the model, we proceed in two steps of Bayesian inference. ...

Hierarchical data structures such as irregular pyramids are used by many applications related to image processing and segmentation. The construction scheme of such pyramids is bottom-up. Such a scheme forbids the definition of a level according to more global information defined at upper levels in the hierarchy. Moreover, the base of the pyramid has to encode any single pixel of the initial ima...

When an image is viewed at decreasing resolutions in a Gaussian pyramid, information is lost gradually. Amid continuous intensity changes across scales, there are “quantum jumps” or “perceptual transitions” in our inner representation. In this paper, we study a representational paradigm called the perceptual scale-space which augments the Gaussian pyramid in traditional image scale-space theory...

We propose a principled convolutional neural pyramid (CNP) framework for general low-level vision and image processing tasks. It is based on the essential finding that many applications require large receptive fields for structure understanding. But corresponding neural networks for regression either stack many layers or apply large kernels to achieve it, which is computationally very costly. O...

The implementation of several pyramid methods on programmable graphics processing units (GPUs) in recent years led to additional research interest in pyramid algorithms for real-time computer graphics. Of particular interest are efficient analysis and synthesis filters based on hardware-supported bilinear texture interpolation because they can be used as building blocks for many GPU-based pyram...

Detecting lines in images using pyramid architecture is the main subject of this paper. The approach is based on the parallel calculation of Hough Transform. A pyramid architecture of size n is a ne-grain architecture with a mesh base of size p n p n processors each holding a single pixel of the image. The pyramid operates in an SIMD mode. Two algorithms for computing the Hough Transform are ex...

Multi-scale manipulations are central to image editing but they are also prone to halos. Achieving artifact-free results requires sophisticated edge-aware techniques and careful parameter tuning. These shortcomings were recently addressed by the local Laplacian filters, which can achieve a broad range of effects using standard Laplacian pyramids. However, these filters are slow to evaluate and ...

In this paper objective is to develop a robust image watermarking method in contourlet domain using GA(Genetic Algorithm) to improve the quality and robustness of the watermarked image, by reducing the (BER)Bit Error Rate to with stand against common image processing attacks. Selecting more Co-efficient in more directions is achieved by means of combining Laplacian Pyramid with Directional filt...

In the paper is presented one new approach for adaptive processing and compression of images of scanned documents, which contain text and pictures. In order to achieve high compression with maximum retained quality, the document content is analyzed and two corresponding regions of interest are set. Then, each region is processed as follows: the text – with lossless and the picture – with lossy ...

Building pyramid for remote sensing (RS) image is an effective way to achieve image multi-resolution organization, and also an important way to improve performance of image browsing. For large-scale remote sensing image, traditional sequential pyramid building processing is a time consuming task in many applications. By taking advantage of multi-core, multi-node cluster computing environment an...