Accuracy Evaluation of Stereo Camera Systems With Generic Camera Models

Rueß, Dominik; Luber, Andreas; Manthey, Kristian; Reulke, Ralf

doi:10.5194/isprsarchives-xxxix-b5-375-2012

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…In addition, it is not generally reversible through the use of re-sampling and any mistake can mean that the image data is unusable. An accuracy analysis for stereo processing with generic camera projection models, with a main aspect on radially induced errors was presented in [91].…”

Section: Data Pre-processingmentioning

confidence: 99%

Reconfigurable architecture for real-time image compression on-board satellites

Manthey

Krutz

Juurlink

2015

J. Appl. Remote Sens

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Data products of optical remote sensing systems are increasingly used in many areas of our everyday life. The spatial as well as the spectral resolution of satellite image data increases steadily with new missions resulting in a higher precision of known procedures and new application scenarios. While the memory capacity requirements can still be fulfilled, the transmission capacity becomes increasingly problematic. Real-time transmission of high-resolution image data is currently not possible.This thesis presents a new image data compression architecture that can be used for current and future projects at the German Aerospace Center (DLR). The architecture has region-of-interest support and offers flexible access to the compressed data based on the CCSDS 122.0-B-1 image data compression standard. Region of interest (ROI) coding can be useful in scenarios where on-board classification, registration, or object or change detection algorithms are used. It is also useful to decrease the amount of data that must be transferred to the ground station. Modifications to the standard have been made to permit a change of compression parameters and the re-organization of the bit-stream after compression. An additional index of the compressed data is created, which makes it possible to locate individual parts of the bit-stream. On request, compressed and stored images can be re-assembled and transmitted according to the application's needs and as requested by the ground station.The requirements, the design of the architecture, and its implementation based on reconfigurable hardware are presented. The architecture was developed for a spacequalified Xilinx Virtex 5QV, where a single instance of the architecture is capable of compressing images at a rate of up to 200 Mpx /s (or 400 Mbyte /s for 16 bit images). It operates at a clock frequency of 100 MHz and processes two image pixels per clock cycle. A Xilinx Virtex-5QV enables thereby compressing images with a width of up to 4096 pixels without the use of external memory. Without external memory and additional interfaces, the power consumption of the architecture is about 5 W. The proposed architecture is one of the fastest implementations yet reported and sufficient for recent high-resolution systems. Investigations in the resource and power consumption, as well as the availability of external storage have shown that it should be possible to integrate the design directly on a focal plane.

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Section: Data Pre-processingmentioning

confidence: 99%

Reconfigurable architecture for real-time image compression on-board satellites

Manthey

Krutz

Juurlink

2015

J. Appl. Remote Sens

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“…The non-iterative algorithms with computational complexity of ( ) O n mainly include: Direct Least Square (DLS) [11], OPnP ( 3 n ≥ ) [12], Direct Linear Transformation (DLT) ( 6 n ≥ ) [13], EPnP ( 4 n ≥ ) [14], A Robust PnP (RPnP) ( 4 n ≥ ) [15]. Due to the first two algorithms have definite objective function, and use algebraic multi-equations to solve this problem, thus the calculation accuracy is high.…”

Section: Introductionmentioning

confidence: 99%

An Improved Orthogonal Iterative Algorithm for Monocular Camera Pose Estimation

Shi¹,

Dong²,

Zheng³

2017

dtcse

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Abstract. In this paper, we focus on the classical perspective-n-point(PnP) problem in monocular camera pose estimation and propose an improved orthogonal iterative algorithm. The key idea is to integrate the steps in each iteration, and extract the repetitive calculation of each iteration. The repetitive computation in each iteration can be abstracted and done before iteration process. The computational complexity of each iteration is reduced from to ( ) O n to (1) O . So that, more iterations can be done in a short time and the accuracy is improved as well. The simulation results and real experiments results show the efficiency and accuracy of our entry accepted iterative algorithms, our algorithm can maintain high pose estimation accuracy. This algorithm is more likely to converge to correct pose in a short run time, which makes it more applicable for real time applications.

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