Analysis of the perceptual quality performance of different HEVC coding tools

Each new video encoding standard includes encoding techniques that aim to improve the performance and quality of the previous standards. During the development of these techniques, PSNR was used as the main distortion metric. However, the PSNR metric does not consider the subjectivity of the human visual system, so that the performance of some coding tools is questionable from the perceptual point of view. To further explore this point, we have developed a detailed study about the perceptual sensibility of different HEVC video coding tools. In order to perform this study, we used some popular objective quality assessment metrics to measure the perceptual response of every single coding tool. The conclusion of this work will help to determine the set of HEVC coding tools that provides, in general, the best perceptual response

Monitoring pest insect traps by means of low-power image sensor technologies

Monitoring pest insect populations is currently a key issue in agriculture and forestry protection. At the farm level, human operators typically must perform periodical surveys of the traps disseminated through the field. This is a labor-, time- and cost-consuming activity, in particular for large plantations or large forestry areas, so it would be of great advantage to have an affordable system capable of doing this task automatically in an accurate and a more efficient way. This paper proposes an autonomous monitoring system based on a low-cost image sensor that it is able to capture and send images of the trap contents to a remote control station with the periodicity demanded by the trapping application. Our autonomous monitoring system will be able to cover large areas with very low energy consumption. This issue would be the main key point in our study; since the operational live of the overall monitoring system should be extended to months of continuous operation without any kind of maintenance (i.e., battery replacement). The images delivered by image sensors would be time-stamped and processed in the control station to get the number of individuals found at each trap. All the information would be conveniently stored at the control station, and accessible via Internet by means of available network services at control station (WiFi, WiMax, 3G/4G, etc.). © 2012 by the authors; licensee MDPI, Basel, Switzerland.This work was partially funded by Ministry of Education and Science grants CTM2011-29691-C02-01, TIN2011-28435-C03-01 and TIN2011-27543-C03-03.López ., O.; Martinez Rach, MO.; Migallon ., H.; Pérez Malumbres, MJ.; Bonastre Pina, AM.; Serrano Martín, JJ. (2012). Monitoring pest insect traps by means of low-power image sensor technologies. Sensors. 12(11):15801-15819. doi:10.3390/s121115801S15801158191211Shelton, A. M., & Badenes-Perez, F. R. (2006). CONCEPTS AND APPLICATIONS OF TRAP CROPPING IN PEST MANAGEMENT. Annual Review of Entomology, 51(1), 285-308. doi:10.1146/annurev.ento.51.110104.150959Jiang, J.-A., Tseng, C.-L., Lu, F.-M., Yang, E.-C., Wu, Z.-S., Chen, C.-P., … Liao, C.-S. (2008). A GSM-based remote wireless automatic monitoring system for field information: A case study for ecological monitoring of the oriental fruit fly, Bactrocera dorsalis (Hendel). Computers and Electronics in Agriculture, 62(2), 243-259. doi:10.1016/j.compag.2008.01.005http://www.memsic.comAl-Saqer. (2011). Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition by Image Processing Techniques. American Journal of Agricultural and Biological Sciences, 6(3), 365-376. doi:10.3844/ajabssp.2011.365.376http://www.ti.com/lit/ds/symlink/cc1110f32.pdfhttp://www.comedia.com.hkOliver, J., & Perez Malumbres, M. (2008). On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements. IEEE Transactions on Circuits and Systems for Video Technology, 18(2), 237-248. doi:10.1109/tcsvt.2007.91396

Improving image compression through the use of evolutionary computing algorithms

Discrete Wavelet Transform has proved to be powerful for image compression because it is able to compact frequency and spatial localization of image energy into a small fraction of coefficients. For a long time it was assumed that there is no compression gain when coding the sign of wavelet coefficients. However, several attempts were carried out and several image encoders like JPEG 2000 include sign coding capabilities. In this paper, we analyze the convenience of including sign coding techniques in tree-based wavelet image encoders, showing their benefits (bit-rate saving). In order to exploit the scarce redundancy of wavelet coefficients sign, we propose the use of machine learning approaches, like evolutionary algorithms, to find the best sign prediction scheme that maximizes the resulting compression rate.We have developed a sign predictionmodule based on the results provided by the evolutionary algorithms, which it is able to work with whatever the tree-based wavelet encoder like SPIHT, LTW, and others. After performing several experiments, we have observed that, by including the proposed sign coding capabilities, the sign compression gain is up to 17%. These results show that sign coding techniques are of interest for improving compression rate, especially when working with large images (2 Mpixel and beyond) at low compression rates (high quality).Thanks to Spanish Ministry of Education and Science under grants TIN2011-27543-C03-03 and TEC2010-11776-E for funding.López-Granado, O.; Galiano, V.; Martí Campoy, A.; Migallón, H.; Martinez Rach, MO.; Piñol, P.; Perez Malumbres, MJ. (2013). Improving image compression through the use of evolutionary computing algorithms. En Data Management and Security: Applications in Medicine, Science and Engineering. Witpress. 37-46. https://doi.org/10.2495/DATA130041S374