Image Mosaicing Using Corner Techniques

Jain, Deepak Kumar; Saxena, Gaurav; Singh, Vineet

doi:10.1109/csnt.2012.27

Cited by 26 publications

(6 citation statements)

References 8 publications

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“…Further, a large area can be easily reconstructed by means of laterally scanning the object in steps of 2 mm × 0.5 mm and recording a single white interferogram at each step and stitching all the single shot interferograms together. An image mosaicing algorithm based on a random corner method was used to stitch the various adjacent interferograms [49]. Figure 10(a) shows the stitched white light interferogram recorded by a color CCD camera.…”

Section: Results and Analysismentioning

confidence: 99%

Single Shot White Light Interference Microscopy for 3D Surface Profilometry Using Single Chip Color Camera

Srivastava

Inam²,

Kumar³

et al. 2016

Journal of the Optical Society of Korea

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We present a single shot low coherence white light Hilbert phase microscopy (WL-HPM) for quantitative phase imaging of Si opto-electronic devices, i.e., Si integrated circuits (Si-ICs) and Si solar cells. White light interferograms were recorded by a color CCD camera and the interferogram is decomposed into the three colors red, green and blue. Spatial carrier frequency of the WL interferogram was increased sufficiently by means of introducing a tilt in the interferometer. Hilbert transform fringe analysis was used to reconstruct the phase map for red, green and blue colors from the single interferogram. 3D step height map of Si-ICs and Si solar cells was reconstructed at multiple wavelengths from a single interferogram. Experimental results were compared with Atomic Force Microscopy and they were found to be close to each other. The present technique is non-contact, full-field and fast for the determination of surface roughness variation and morphological features of the objects at multiple wavelengths.

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Section: Results and Analysismentioning

confidence: 99%

Single Shot White Light Interference Microscopy for 3D Surface Profilometry Using Single Chip Color Camera

Srivastava

Inam²,

Kumar³

et al. 2016

Journal of the Optical Society of Korea

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“…The method of combining photographs of the same scene into a broad picture is known as image mosaicking. The union of two input images would be the product of the image mosaic process [27].…”

Section: Table-1: Details Of Satellite Images Used In the Workmentioning

confidence: 99%

Land Use Land Cover Study of Sentinel-2A and Landsat-5 Images Using NDVI and Supervised Classification Techniques

Makandar¹,

Kaman²

2021

CIML

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Land Use Land Cover (LULC) change monitoring plays very significant role in planning, policy making, management programs required for development activities at regional levels of any country. This study is an attempt to monitor LULC change of Vijayapura taluk, Karnataka, India for the period of 25 years from 1995 to 2021 using Remote Sensing (RS) and Geographic Information System (GIS). Satellite Images from Sentinel-2A MSI (Multispectral Imager), Landsat-5TM (Thematic Mapper) are used to generate LULC maps. Vegetation Change in the study area is computed using Normalized Difference Vegetation Index (NDVI) and results show that vegetation rate is increased from 0.6% in 1995 to 27.5% in 2021. Supervised Classification is carried out by using Maximum Likelihood Classification (MLC). 5 major classes considered for classification are namely: Waterbodies, Cropland/Vegetation, Fallow Land, Built-up Area and Barren Land. ArcGIS software tool is used for implementing the proposed study. Google Earth Pro used for accuracy assessment which is done by taking ground truth values for corresponding Classifications. Results show that the proposed system is able to achieve 88.16% of overall accuracy. Keyword : Land Use Land Cover, Supervised Classification, Remote Sensing, Maximum Likelihood Classification, Normalized Difference Vegetation Index, High Resolution, Multitemporal, Satellite Images.

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“…Meanwhile, an adaptive uniform distribution SURF algorithm for image stitching by reduced the computation complexity suitable for image matching [9]. An image mosaic algorithm is based on a random corner method [11]. The study avoided corner redundancy and removed false matched corner pair effectively.…”

Section: Related Workmentioning

confidence: 99%

Feature-based Automatic Image Stitching Using SIFT, KNN and RANSAC

Caparas¹

2020

IJATCSE

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Image panorama is a process of combining two or more images to form one single image. Image stitching is a process of creating image panorama from a set of images with overlapped fields. Image stitching faces many challenges such as images corrupted by noise, indexing a large number of images, high image resolution, and presence of parallax and scene motion. The problem in eliminating visible seam is also another challenge. To obtain a wide seamless panorama, this paper implemented a feature-based automatic image stitching algorithm. The image stitching model consists of five stages: image registration, features detection, feature matching, Homography estimation, and image blending. A method of creating a seamless image panorama was introduced where the scale-invariant features transform (SIFT) was used for image feature extraction, the K-nearest neighbor algorithm for feature matching, the Random sample consensus (RANSAC) for image warping calculating homography and the weighted matrix was intended for image blending. Three (3) sets of source images were used to test for stitching demo. The effectiveness of the stitching method was defined by comparing the resulting panorama to a predicted reference image using the percent image similarity defined as the proportion between the matches found and keypoints. For all of the testing sets, the resulting percent similarity with respect to the reference image ranges from 12-18%. This is due to the fact that high-quality images (i.e. high number of pixels) have thousands of features -hence, thousands of keypoints while low-quality images may have only a few hundreds.

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Image Mosaicing Using Corner Techniques

Cited by 26 publications

References 8 publications

Single Shot White Light Interference Microscopy for 3D Surface Profilometry Using Single Chip Color Camera

Single Shot White Light Interference Microscopy for 3D Surface Profilometry Using Single Chip Color Camera

Land Use Land Cover Study of Sentinel-2A and Landsat-5 Images Using NDVI and Supervised Classification Techniques

Feature-based Automatic Image Stitching Using SIFT, KNN and RANSAC

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