scholarly journals HOLBP: Remote Sensing Image Registration Based on Histogram of Oriented Local Binary Pattern Descriptor

2021 ◽  
Vol 13 (12) ◽  
pp. 2328
Author(s):  
Yameng Hong ◽  
Chengcai Leng ◽  
Xinyue Zhang ◽  
Zhao Pei ◽  
Irene Cheng ◽  
...  
Keyword(s):  
Image Registration ◽  
Local Binary Pattern ◽  
Computational Time ◽  
Rotation Invariant ◽  
Edge Information ◽  
Important Research Topic ◽  
New Construction ◽  
Novel Method ◽  
Direction Information ◽  
Angle Calculation

Image registration has always been an important research topic. This paper proposes a novel method of constructing descriptors called the histogram of oriented local binary pattern descriptor (HOLBP) for fast and robust matching. There are three new components in our algorithm. First, we redefined the gradient and angle calculation template to make it more sensitive to edge information. Second, we proposed a new construction method of the HOLBP descriptor and improved the traditional local binary pattern (LBP) computation template. Third, the principle of uniform rotation-invariant LBP was applied to add 10-dimensional gradient direction information to form a 138-dimension HOLBP descriptor vector. The experimental results showed that our method is very stable in terms of accuracy and computational time for different test images.

scholarly journals Azimuth Ambiguity Suppression in SAR Images Based on VS-KSVD Dictionary Learning and Compressive Sensing

2021 ◽  
Vol 2083 (3) ◽  
pp. 032049
Author(s):  
Xinchang Hu ◽  
Pengbo Wang ◽  
Yanan Guo ◽  
Qian Han ◽  
Xinkai Zhou
Keyword(s):  
Dictionary Learning ◽  
Image Interpretation ◽  
Statistical Characteristics ◽  
Sar Images ◽  
Edge Information ◽  
Frequency Domains ◽  
Under Sampling ◽  
High Resolution Images ◽  
Novel Method

Abstract The azimuth ambiguities appear widely in Synthetic Aperture Radar (SAR) images, which causes a large number of false targets and seriously affect the quality of image interpretation. Due to under-sampling in Doppler domain, ambiguous energy is mixed with energy from the main zone in the time and frequency domains. In order to effectively suppress the ambiguous energy in SAR images without loss of resolution, this paper presents a novel method of KSVD dictionary learning based on variance statistics (VS-KSVD) and compressed sensing (CS) reconstruction. According to the statistical characteristics of distributed targets, the dictionary that represents the ambiguities is selected and suppressed by coefficient weighting, in which local window filtering is carried out to remove the block effect and optimize the edge information. Finally, the high resolution images with low-ambiguity can be reconstructed by CS. With the proposed approach, the feasibility and effectiveness of the proposed approach is validated by using satellite data and simulation in suppressing azimuth ambiguity.

Rotation-Invariant Image and Video Description With Local Binary Pattern Features

2012 ◽  
Vol 21 (4) ◽  
pp. 1465-1477 ◽  
Author(s):  
Guoying Zhao ◽  
T. Ahonen ◽  
J. Matas ◽  
M. Pietikainen
Keyword(s):  
Local Binary Pattern ◽  
Rotation Invariant ◽  
Video Description

Both Hands’ Fingers’ Angle Calculation from Live Video

2012 ◽  
Vol 2 (2) ◽  
pp. 1-11 ◽  
Author(s):  
Ankit Chaudhary ◽  
Jagdish L. Raheja ◽  
Karen Das ◽  
Shekhar Raheja
Keyword(s):  
Gesture Recognition ◽  
Color Space ◽  
Three Dimensional ◽  
Region Of Interest ◽  
Natural Computing ◽  
Robotic Hand ◽  
Hsv Color Space ◽  
Binary Format ◽  
Novel Method ◽  
Angle Calculation

In the last few years gesture recognition and gesture-based human computer interaction has gained a significant amount of popularity amongst researchers all over the world. It has a number of applications ranging from security to entertainment. Gesture recognition is a form of biometric identification that relies on the data acquired from the gesture depicted by an individual. This data, which can be either two-dimensional or three-dimensional, is compared against a database of individuals or is compared with respective thresholds based on the way of solving the riddle. In this paper, a novel method for angle calculation of both hands’ bended fingers is discussed and its application to a robotic hand control is presented. For the first time, such a study has been conducted in the area of natural computing for calculating angles without using any wired equipment, colors, marker or any device. The system deploys a simple camera and captures images. The pre-processing and segmentation of the region of interest is performed in a HSV color space and a binary format respectively. The technique presented in this paper requires no training for the user to perform the task.

A novel method for automatic image registration based on wavelet and near fuzzy set

2013 ◽  
Author(s):  
Somoballi Ghoshal ◽  
Pubali Chatterjee ◽  
Biswajit Biswas ◽  
Amlan Chakrabarti ◽  
Kashi Nath Dey
Keyword(s):  
Image Registration ◽  
Fuzzy Set ◽  
Novel Method

A method for reducing of computational time on image registration employing wavelet transformation

2007 ◽  
Author(s):  
Yutaro Yamamura ◽  
Hyoungseop Kim ◽  
Joo kooi Tan ◽  
Seiji Ishikawa ◽  
Akiyoshi Yamamoto
Keyword(s):  
Image Registration ◽  
Wavelet Transformation ◽  
Computational Time

scholarly journals miRID: Multi-Modal Image Registration Using Modality-Independent and Rotation-Invariant Descriptor

Symmetry ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2078
Author(s):  
Thuvanan Borvornvitchotikarn ◽  
Werasak Kurutach
Keyword(s):  
Image Processing ◽  
Image Registration ◽  
Similarity Measures ◽  
Fundamental Property ◽  
Transformation Process ◽  
Experimental Result ◽  
Absolute Difference ◽  
Rotation Invariant ◽  
The Mean ◽  
Image Registrations

Axiomatically, symmetry is a fundamental property of mathematical functions defining similarity measures, where similarity measures are important tools in many areas of computer science, including machine learning and image processing. In this paper, we investigate a new technique to measure the similarity between two images, a fixed image and a moving image, in multi-modal image registration (MIR). MIR in medical image processing is essential and useful in diagnosis and therapy guidance, but still a very challenging task due to the lack of robustness against the rotational variance in the image transformation process. Our investigation leads to a novel, local self-similarity descriptor, called the modality-independent and rotation-invariant descriptor (miRID). By relying on the mean of the intensity values, an miRID is simply computable and can effectively handle the complicated intensity relationship between multi-modal images. Moreover, it can also overcome the problem of rotational variance by sorting the numerical values, each of which is the absolute difference between each pixel’s intensity and the mean of all pixel intensities within a patch of the image. The experimental result shows that our method outperforms others in both multi-modal rigid and non-rigid image registrations.

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