A modified spatially adaptive denoising algorithm for a single image corrupted by Gaussian noise is proposed in this paper. The proposed algorithm use local statistics of a selected window i.e. by defining local weighted mean, local weighted activity and local maximum. These local statistics are used to detect the noise in the image then a modified Gaussian filter is used for noise suppression....

Image blending is very important for image stitching with visible seams. An effective blending method for panoramic images in image-based virtual reality is proposed in this paper. The proposed blending method is a two-phase scheme. The histogram-based blending is first applied in the first phase scheme; and then in the second phase scheme, the weighted blending is used under the result of the ...

Contourlet transform is an effective solution to solve two or more dimensional singularity and has good direction and anisotropy. Against the shortage of ability of describing the spatial distribution characteristic of object’s edge information, this paper proposed a new image retrieval algorithm based on Contourlet transform, which blocks the indexed image and decomposes each sub-block images ...

This paper focuses on a noise filtering in color image sequences, where a new class of center-weighted vector directional filters is provided. According to high dimensionality of color image sequences, where besides the spatial frequencies in the frames it is necessary to consider the temporal correlation of an image sequence and the correlation between color channels too, the processing of col...

Image blurring is one of the major problems in the field of digital image processing. Generally, camera shake causes blurring. As a result, uneven blur kernel is present in the image which is random in nature. Therefore, every image in the burst is blurred in a different way. Deblurred image can be obtained using single image or multiple images. A clean sharp image is recovered by fusing the gr...

Assets have different shapes, colors and textures. A shape feature is the main characteristic, which distinguishes each type of asset in addition to the other features, i.e. the color and the texture. The value of features in the image-based asset information retrieval is used as the key field by comparing the similarities between the images. These similarities can be determined based on the di...

High feature vector dimension quietly remained a curse element for Content Based Image Retrieval (CBIR) system which eventually degrades its efficiency while indexing similar images from database. This paper proposes CBIR system using Gray Scale Weighted Average technique for reducing the feature vector dimension. The proposed method is more suitable for color and texture image feature analysis...

In this paper, we present an image understanding algorithm for automatically identifying and ranking different image regions into several levels of importance. Given a color image, specialized maps for classifying image content namely: weighted similarity, weighted homogeneity, image contrast and memory colors are generated and combined to provide a metric for perceptual importance classificati...

In this paper we introduce a novel line detection algorithm based on a weighted minimum mean square error (MSE) formulation. This algorithm has been developed to enable an autonomous robot to follow a white line drawn on the floor, but is general in nature and widely applicable to line detection problems. Traditional approaches to line detections consist of two stages, an edge detection stage a...

The hashing methods have attracted much attention for large scale image retrieval. Some deep hashing methods have achieved promising results by taking advantage of the better representation power of deep networks recently. However, existing deep hashing methods treat all hash bits equally. On one hand, a large number of images share the same distance to a query image because of the discrete Ham...