Abstract
In digital camera, it’s difficult to exceed the dynamic range of 60~80dB because of the saturation current and background noise of CCD/CMOS image sensor in a single exposure image. In order to obtain more information and detail of a scene, we should extend its dynamic range, which was called HDR technology. Recent years, HDR imaging techniques have become the focus of much research because of their high theoretical and practical importance. By applying HDR techniques, the performance of different image processing and computer vision algorithms, information enhancement, and object and pattern recognition can also be improved. In this paper, a new tone reproduction algorithm is introduced, based on which may help to develop the hard-to-view or nonviewable features and details of color images. This method applies on multi-exposure images synthesis technique, where the red, green, and blue (RGB) color components of the pixels are separately handled. In the output, the corresponding (modified) color components are blended. As a result, a high quality HDR image is obtained, which contains almost the whole details and color information.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cvetković, S., Klijn, J., De With, P.H.N.: Tone-Mapping Functions and Multiple-Exposure Techniques for High Dynamic-Range Images. IEEE Transactions on Consumer Electronics 54(2), 904–911 (2008)
Várkonyi-Kóczy, A.R., Rövid, A., Hashimoto, T.: Gradient-Based Synthesized Multiple Exposure Time Color HDR Image. IEEE Transactions on Instrumentation and Measurement 57(8), 1779–1785 (2008)
Várkonyi-Kóczy, A.R.: Improved fuzzy logic supported HDR colored information enhancement. In: I2MTC-International Instrumentation and Measurement Technology Conference, Singapore, pp. 361–366 (2009)
Goshtasby, A.A.: Fusion of multi-exposure images. Image and Vision Computing 23(6), 611–618 (2005)
Russo, F.: Fuzzy filtering of noisy sensor data. In: Proc. of the IEEE Instrumentation and Measurement Technology Conference, Brussels, Belgium, pp. 1281–1285 (1996)
Russo, F.: Recent advances in fuzzy techniques for image enhancement. IEEE Transactions on Instrumentation and Measurement 47(6), 1428–1434 (1998)
Adelson, E.H., Pentland, A.P.: The Perception of Shading and Reflectance. In: Knill, D., Richards, W. (eds.) Perception as Bayesian Inference, pp. 409–423. Cambridge University Press, New York (1996)
Rovid, A., Varlaki, P.: Method for Merging Multiple Exposure Color Image Data. In: International Conference on Intelligent Engineering Systems, pp. 27–31 (2009)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, H., Cao, J., Tang, L., Tang, Y. (2011). HDR Image Synthesis Based on Multi-exposure Color Images. In: Tan, H. (eds) Informatics in Control, Automation and Robotics. Lecture Notes in Electrical Engineering, vol 132. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25899-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-642-25899-2_16
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25898-5
Online ISBN: 978-3-642-25899-2
eBook Packages: EngineeringEngineering (R0)