3 research outputs found

    Photographic Noise Performance Measures Based on RAW Files Analysis of Consumer Cameras

    Full text link
    [EN] Photography is being benefited from the huge improvement in CMOS image sensors. New cameras extend the dynamic range allowing photographers to take photos with a higher quality than they could imagine one decade ago. However, the existence of different technologies make more complicated the photographic analysis of how to determine the optimal camera exposure settings. In this paper, we analyze how the different noise models are translated to different signal to noise SNR curve patterns and which factors are relevant. In particular, we discuss profoundly the relationships between exposure settings (shutter speed, aperture and ISO). Since a fair comparison between cameras can be tricky because of different pixel size, sensor format or ISO scale definition, we explain how the pixel analysis of a camera can be translated to a more helpful universal photographic noise measure based on human perception and common photography rules. We analyze the RAW files of different camera models and show how the noise performance analysis (SNR and dynamic range) interact with photographer's requirements.Igual García, J. (2019). Photographic Noise Performance Measures Based on RAW Files Analysis of Consumer Cameras. Electronics. 8(11):1-30. https://doi.org/10.3390/electronics8111284S130811Camera Imaging Products Association: Digital Cameras Reporthttp://cipa.jp/stats/dc_e.htmlGye, L. (2007). Picture This: the Impact of Mobile Camera Phones on Personal Photographic Practices. Continuum, 21(2), 279-288. doi:10.1080/10304310701269107Bhandari, A., & Raskar, R. (2016). Signal Processing for Time-of-Flight Imaging Sensors: An introduction to inverse problems in computational 3-D imaging. IEEE Signal Processing Magazine, 33(5), 45-58. doi:10.1109/msp.2016.2582218Wang, J., Zhang, C., & Hao, P. (2011). New color filter arrays of high light sensitivity and high demosaicking performance. 2011 18th IEEE International Conference on Image Processing. doi:10.1109/icip.2011.6116336Chan, C.-C., & Chen, H. H. (2018). Improving the Reliability of Phase Detection Autofocus. Electronic Imaging, 2018(5), 241-1-241-5. doi:10.2352/issn.2470-1173.2018.05.pmii-241Kirkpatrick, K. (2019). The edge of computational photography. Communications of the ACM, 62(7), 14-16. doi:10.1145/3329721Koppal, S. J. (2016). A Survey of Computational Photography in the Small: Creating intelligent cameras for the next wave of miniature devices. IEEE Signal Processing Magazine, 33(5), 16-22. doi:10.1109/msp.2016.2581418CMOS Image Sensor Market: Forecasts from 2019 to 2024https://www.knowledge-sourcing.com/report/cmos-Image-sensor-marketPhotonstophotos.nethttp://photonstophotos.netDxomarkhttp://dxomark.comBoukhayma, A., Peizerat, A., & Enz, C. (2016). Temporal Readout Noise Analysis and Reduction Techniques for Low-Light CMOS Image Sensors. IEEE Transactions on Electron Devices, 63(1), 72-78. doi:10.1109/ted.2015.2434799Vargas-Sierra, S., Linán-Cembrano, G., & Rodríguez-Vázquez, A. (2015). A 151 dB High Dynamic Range CMOS Image Sensor Chip Architecture With Tone Mapping Compression Embedded In-Pixel. IEEE Sensors Journal, 15(1), 180-195. doi:10.1109/jsen.2014.2340875Hassan, N. B., Huang, Y., Shou, Z., Ghassemlooy, Z., Sturniolo, A., Zvanovec, S., … Le-Minh, H. (2018). Impact of Camera Lens Aperture and the Light Source Size on Optical Camera Communications. 2018 11th International Symposium on Communication Systems, Networks & Digital Signal Processing (CSNDSP). doi:10.1109/csndsp.2018.8471766Hirsch, J., & Curcio, C. A. (1989). The spatial resolution capacity of human foveal retina. Vision Research, 29(9), 1095-1101. doi:10.1016/0042-6989(89)90058-8ColorChecker Classic Charthttps://xritephoto.com/colorchecker-classicWang, F., & Theuwissen, A. (2017). Linearity analysis of a CMOS image sensor. Electronic Imaging, 2017(11), 84-90. doi:10.2352/issn.2470-1173.2017.11.imse-191Wakashima, S., Kusuhara, F., Kuroda, R., & Sugawa, S. (2015). Analysis of pixel gain and linearity of CMOS image sensor using floating capacitor load readout operation. Image Sensors and Imaging Systems 2015. doi:10.1117/12.2083111Wang, F., Han, L., & Theuwissen, A. J. P. (2018). Development and Evaluation of a Highly Linear CMOS Image Sensor With a Digitally Assisted Linearity Calibration. IEEE Journal of Solid-State Circuits, 53(10), 2970-2981. doi:10.1109/jssc.2018.285625
    corecore