A Gabor Odd Filter-Based Ratio Operator for SAR Image Matching

Paul, Sourabh; Pati, Umesh Chandra

doi:10.1109/lgrs.2018.2872979

Cited by 17 publications

(9 citation statements)

References 15 publications

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“…The ratio‐based operator is generally used to compute the gradients. In [26, 27], it is mentioned that the GOFRO is comparatively more robust than the other ratio operators in the presence of speckle noise. So, in our proposed method, it has been used to compute the gradients for the multi‐scale Harris function.…”

Section: Proposed Methodsmentioning

confidence: 99%

Automatic optical‐to‐SAR image registration using a structural descriptor

Paul

Pati

2020

IET Image Processing

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Section: Proposed Methodsmentioning

confidence: 99%

Automatic optical‐to‐SAR image registration using a structural descriptor

Paul

Pati

2020

IET Image Processing

Self Cite

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“…where β 1 , β 2 , and β 3 are the modulation dependent parameters expressed in Table 2, and Q ( . ) represents the Gaussian Q function which gives the area under the tail of a Gaussian curve and is defined as follows: 39–42…”

Section: End-to-end Symbol Error Analysismentioning

confidence: 99%

Examination of the multiple-input multiple-output space-time block-code selective decode and forward relaying protocol over non-homogeneous fading channel conditions

Shankar¹,

Krishna

R³

2021

Journal of Defense Modeling & Simulation

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With the tremendous increase in wireless user traffic, investigation on the end-to-end reliability of wireless networks in practical conditions such as non-homogeneous fading channel conditions is becoming increasingly widespread. Because they fit well to the experimental data, generalized channel fading distributions like κ–μ are well suited for modeling diverse fading channels. This paper analyzes the symbol error rate (SER) and outage probability (OP) performance of multiple-input multiple-output (MIMO) space-time block-code (STBC) selective decode and forward (S-DF) network over κ–μ fading channel conditions considering the additive white Gaussian noise (AWGN). First, the closed-form (CF) analytical expressions for the probability density function (PDF) and the cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) as well as its moment generating function (MGF) are derived. Second, the OP performance is then investigated for various values of the channel fading parameter and SNR regimes. The simulation findings show an increase in SER performance with an improved line-of-sight (LOS) component. Furthermore, the results show that the S-DF relaying systems can function properly even when there is no fading or LOS component. The OP has been increasing with the increase in the value of μ and κ. In medium and high SNR regimes, simulation results exactly match with analytical results.

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“…We start from the keypoint detection stage. It is obvious that evenly-distributed keypoints show a high possibility to obtain sufficient correspondences, which can improve the registration accuracy of the transformation model [39]. We first utilize the block-harris method to extract corner points.…”

Section: A Keypoint Detectionmentioning

confidence: 99%

Automatic Registration of Optical and SAR Images Via Improved Phase Congruency Model

Xiang

Tao

Wang

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In this paper, we propose an automatic and efficient method to solve optical and SAR image registration using the improved phase congruency (PC) model. First, evenly-distributed keypoints are extracted from the optical images via the block harris method. Complementary grid points are then selected in image regions with poor structural information and supplemented to the keypoint set. For each keypoint, a robust feature representation that captures the local spatial relationship is proposed based on the improved PC model. Specifically, we propose to use two different PC models, the classic PC and the SAR-PC, to construct features for optical and SAR images respectively. The PC features of several directions are aggregated to construct the feature descriptors, and a similarity metric via the phase correlation of feature descriptors is obtained. The proposed similarity metric can not only find accurate correspondence but also present efficient results without presetting the size of the search region. We compare the proposed method with two baselines and stateof-the-art (SOTA) methods, i.e. OS-SIFT, HOPC, CFOG, in various scenarios. The results show that the proposed method outperforms the baselines and shows comparable performance with SOTA methods in regions with abundant structural information and better performance in regions with less structural information. Moreover, we build a high-resolution optical and SAR image matching dataset, which consists of 10,692 nonoverlapping patch-pairs of 256 × 256 pixels and 1-m resolution. Results of two benchmarks, Siamese deep matching network and conditional Generative Adversarial Networks, show that this dataset is practical and challenging.

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A Gabor Odd Filter-Based Ratio Operator for SAR Image Matching

Cited by 17 publications

References 15 publications

Automatic optical‐to‐SAR image registration using a structural descriptor

Automatic optical‐to‐SAR image registration using a structural descriptor

Examination of the multiple-input multiple-output space-time block-code selective decode and forward relaying protocol over non-homogeneous fading channel conditions

Automatic Registration of Optical and SAR Images Via Improved Phase Congruency Model

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