2D image mosaic building 2D3 - Ifremer

More documents

Recommendations

Info

1. INTRODUCTION Project Exocet/D page 4/16 In this report, we address the issue of managing seabed video records. During at sea trials, a lot of video is recorded by scientists who need it to analyze the ocean floor. Because of the storage capacity increase, the number of video records always increases during at sea trials. That leads scientists to spend more and more time on analyzing video records. The aim of video mosaicing is then to propose a tool to obtain a map whose extend is far larger than the camera field of view to enable the scientist to have a global view of the scene, and at the same time to reduce and compress the video storage capacity. 2. WHAT IS A GEO-REFERENCED VIDEO MOSAIC? In order to simplify the work of the scientists concerning the exploitation of the numerous video DVD’s resulting from at sea trials, we have been led to develop a tool to provide a larger view of the seabed than the restricted field of view of a video camera. The aim of video mosaicing is then to build images whose extend is far larger than the snapshot of a video recording. The resulting image represents a larger area of the seabed and is called a mosaic. The principle used to build mosaics is quite simple to understand. When the video stream is acquired, it can be seen as a succession of images which have a great part in common. The idea is to estimate the part which has been added from one image to another. The new part of the current image is added and merged with the previous image. Every N images, a mosaic is built and another one can begin. This step is performed by image processing techniques. The other main issue of video mosaicing is to locate the mosaics on the seabed so that the scientists can deal the mosaics with other geo-referenced data such as bathymetry, samples, physical or chemical data. This can be done by two ways. In the simplest case, the operator gives the positioning, heading and altitude of the first point and then the mosaic location is calculated by image processing. But this way is not the best one since errors due to image processing occur and accumulate through the whole process. So, to overcome this drawback, the other means consists in merging navigation data with image. The whole process is developed in the following part but is summarized in the sketch hereafter (Figure 1). Deliverable N° 2D3 Report on image mosaic building DOP/CM/SM/PRAO/06.224 Grade : 1.0 27/09/2006
Image1 Image2 Image3 ……… 3. MOSAICING ALGORITHMS Project Exocet/D page 5/16 (X0,Y0) 1 mosaic built from 3 images (X0,Y0) (X1,Y1) Figure 1: Illustration of video mosaicing 2 mosaics built from 3 images each Many image processing techniques allow us to calculate the geometric relationship between two images. Hereafter two different methods have been investigated and integrated into the MATISSE Software® which has been developed at IFREMER. The first one relies on a feature tracking algorithm (KLT) while the second one, the RMR method, estimates the movement by a robust optical flow algorithm. Both algorithms estimate a displacement in pixels between two successive images. In order to provide the mosaics with metric dimension, the displacement in pixels needs to be converted into meters. This step is performed using the camera parameters and the altitude provided by navigation. 3.1. KLT algorithm 3.1.1. Principle This algorithm is based upon researches performed by Kanade, Lucas and Tomasi (KLT). It consists in detecting and tracking point features through an image stream [SHI94]. The points are selected if they meet a criterion which characterizes a locally textured area. Then, the points are tracked through the sequence. When a list of matched points is obtained from successive images, a global displacement is computed to register the successive images and to build a mosaic. Deliverable N° 2D3 Report on image mosaic building DOP/CM/SM/PRAO/06.224 Grade : 1.0 27/09/2006
Page 1 and 2: Underwater Systems Department A.G.
Page 3: Deliverable N° 2D3 Report on image
Page 7 and 8: We can note that J ( x) = I( x −
Page 9 and 10: Project Exocet/D page 9/16 This est
Page 11 and 12: 3.3.4. Intrinsic parameters estimat
Page 13 and 14: Time update equations (“predict
Page 15 and 16: 4.2. User interface Project Exocet/

2D image mosaic building 2D3 - Ifremer

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?