scholarly journals A Robust Image Mosaicing Technique Using Frequency Domain

2018 ◽  
Vol 6 (1) ◽  
pp. 1-8
Author(s):  
Sarabpreet Kaur ◽  
Jyoti Patel
Keyword(s):  
Image Registration ◽  
Frequency Domain ◽  
Spatial Domain ◽  
Field Of View ◽  
Computationally Efficient ◽  
Illumination Variation ◽  
Image Mosaicing ◽  
Robustness To Noise ◽  
Robust Image

Image mosaicing is the process of joining small images of the same scene which may be clicked at different times, with different cameras, or illumination variation and produce the image with bigger field of view. The leading contribution of the paper lies in the primary detection of features using SURF which completely works in the spatial domain. For image registration frequency based approach has been used. The proposed approach is global, has robustness to noise and is computationally efficient.

scholarly journals Fractional Regularization Term for Variational Image Registration

2009 ◽  
Vol 2009 ◽  
pp. 1-13 ◽  
Author(s):  
Rafael Verdú-Monedero ◽  
Jorge Larrey-Ruiz ◽  
Juan Morales-Sánchez ◽  
José Luis Sancho-Gómez
Keyword(s):  
Image Registration ◽  
Frequency Domain ◽  
Energy Functional ◽  
Spatial Domain ◽  
Gradual Transition ◽  
Lagrange Equations ◽  
Simple Formulation ◽  
Regularization Term ◽  
Classical Formulation ◽  
Variational Image

Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.

Fast and robust image watermarking method in the spatial domain

2020 ◽  
Author(s):  
Zihan Yuan ◽  
Qingtang Su ◽  
Decheng Liu ◽  
Xueting Zhang ◽  
Tao Yao
Keyword(s):  
Image Watermarking ◽  
Spatial Domain ◽  
Robust Image

scholarly journals A computationally efficient approach for template matching-based image registration

Sadhana ◽  
2014 ◽  
Vol 39 (2) ◽  
pp. 317-331 ◽  
Author(s):  
VILAS H GAIDHANE ◽  
YOGESH V HOTE ◽  
VIJANDER SINGH
Keyword(s):  
Image Registration ◽  
Template Matching ◽  
Computationally Efficient ◽  
Efficient Approach

scholarly journals AUTOMATED MOSAICKING OF GEOSTATIONARY OCEAN COLOR IMAGER BY COMBINATION OF SPATIAL AND FREQUENCY MATCHING

2018 ◽  
Vol XLII-2 ◽  
pp. 495-499
Author(s):  
H. G. Kim ◽  
J. H. Son ◽  
T. Kim
Keyword(s):  
Frequency Domain ◽  
Spatial Domain ◽  
Geometric Distortion ◽  
Future Research ◽  
Geometric Correction ◽  
Frequency Matching ◽  
Image Mosaicking ◽  
Important Processing ◽  
Sensor Modelling

In general, image mosaicking is a useful and important processing for handling images with narrow field of view. It is being used widely for images from commercial cameras as well as from aerial and satellite cameras. For mosaicking images with geometric distortion, geometric correction of each image should be performed before combining images. However, automated mosaicking images with geometric distortion is not a trivial task. The goal of this paper is the development of automated mosaicking techniques applicable to handle GOCI images. In this paper, we try to extract tie-points by using spatial domain and frequency domain matching and perform the mosaicking of GOCI. The method includes five steps. First, we classify GOCI image slots according to the existence of shorelines by spatial domain matching. Second, we perform precise geometric correction on the slots with shorelines. Third, we perform initial sensor modelling for the slots without shorelines and apply geometric correction based on the initial model. Fourth, the relative relationship between the slots without shorelines and the slots with shorelines is estimated through frequency domain matching. Lastly, mosaicking of geometrically corrected all 16 image slots is performed. The proposed method was verified by applying to real GOCI images. The proposed method was able to perform automated mosaicking even for images without shorelines, and its accuracy and processing time were satisfactory. For future research, we will improve frequency matching to generate multiple tie-points and to analyse the applicability of precise sensor modelling directly from frequency matching. It is expected that the proposed method can be applied to the follow-up sensor of the GOCI, GOCI-II, and other ocean satellite images.

scholarly journals STUDI DAN IMPLEMENTASI STEGANOGRAFI METODE ALGORITMA DAN TRANSFORMASI PADA CITRA JPEG

Teknika ◽  
2013 ◽  
Vol 2 (1) ◽  
pp. 46-58
Author(s):  
Timothy John Pattiasina
Keyword(s):  
Frequency Domain ◽  
Wavelet Transformation ◽  
Spatial Domain ◽  
Discrete Cosine Transformation ◽  
Cosine Transformation

Steganografi adalah seni dan ilmu menulis atau menyemhunyikan pesan tersembunyi dengan suatu cara sehingga selain si pengirim dan si penerima, tidak ada seorangpun yang mengetahui atau menyadari bahwa ada suatu pesan rahasia. lstilah steganografi termasuk penyemhunyian data digital dalam komputer Ada beberapa metode steganografi, salah satunya adalah metode Algorithms and Transformation. Metode menyembunyikan data dalam fungsi matematika yang disebut algoritma compression. Dua fungsi tersebut adalah Discrete Cosine Transformation (DCT) dan Wavelet Transformation. Fungsi DCT dan Wavelet yaitu untuk mentransformasikan data dari satu tempat (domain) ke tempat (domain) yang lain. Fungsi DCT yaitu mentransformasi data dari tempat spatial (spatial domain) ke tempat fiekuensi (frequency domain).

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