Green compressive sampling reconstruction in IoT networks

In this paper, we address the problem of green Compressed Sensing (CS) reconstruction within Internet of Things (IoT) networks, both in terms of computing architecture and reconstruction algorithms. The approach is novel since, unlike most of the literature dealing with energy efficient gathering of the CS measurements, we focus on the energy efficiency of the signal reconstruction stage given the CS measurements. As a first novel contribution, we present an analysis of the energy consumption within the IoT network under two computing architectures. In the first one, reconstruction takes place within the IoT network and the reconstructed data are encoded and transmitted out of the IoT network; in the second one, all the CS measurements are forwarded to off-network devices for reconstruction and storage, i.e., reconstruction is off-loaded. Our analysis shows that the two architectures significantly differ in terms of consumed energy, and it outlines a theoretically motivated criterion to select a green CS reconstruction computing architecture. Specifically, we present a suitable decision function to determine which architecture outperforms the other in terms of energy efficiency. The presented decision function depends on a few IoT network features, such as the network size, the sink connectivity, and other systems’ parameters. As a second novel contribution, we show how to overcome classical performance comparison of different CS reconstruction algorithms usually carried out w.r.t. the achieved accuracy. Specifically, we consider the consumed energy and analyze the energy vs. accuracy trade-off. The herein presented approach, jointly considering signal processing and IoT network issues, is a relevant contribution for designing green compressive sampling architectures in IoT networks

Fusion of Global and Local Motion Estimation Using Foreground Objects for Distributed Video Coding

International audienceThe side information in distributed video coding is estimated using the available decoded frames, and exploited for the decoding and reconstruction of other frames. The quality of the side information has a strong impact on the performance of distributed video coding. Here we propose a new approach that combines both global and local side information to improve coding performance. Since the background pixels in a frame are assigned to global estimation and the foreground objects to local estimation, one needs to estimate foreground objects in the side information using the backward and forward foreground objects, The background pixels are directly taken from the global side information. Specifically, elastic curves and local motion compensation are used to generate the foreground objects masks in the side information. Experimental results show that, as far as the rate-distortion performance is concerned, the proposed approach can achieve a PSNR improvement of up to 1.39 dB for a GOP size of 2, and up to 4.73 dB for larger GOP sizes, with respect to the reference DISCOVER codec. Index Terms A. ABOU-ELAILAH, F. DUFAUX, M. CAGNAZZO, and B. PESQUET-POPESCU are with the Signal and Image Processin

Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

International audienceMultispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields

An Enhanced Approach of Image Steganographic Using Discrete Shearlet Transform and Secret Sharing

               في الآونة الأخيرة، جعل الإنترنت المستخدمين قادرين على نقل الوسائط الرقمية بطريقة أسهل. على الرغم من هذه السهولة للإنترنت، إلا أنه قد تؤدي إلى العديد من التهديدات التي تتعلق بسرية محتويات الوسائط المنقولة مثل مصادقة الوسائط والتحقق من تكاملها. لهذه الأسباب ، يتم استخدام أساليب إخفاء البيانات والتشفير لحماية محتويات الوسائط الرقمية. في هذه الورقة البحثية ، تم اقتراح طريقة معززة لإخفاء المعلومات بالصور مع التشفير المرئي. يتم تشفير الشعار السري (صورة ثنائية) بالحجم (128 × 128) عن طريق تطبيق التشفير البصري (2 out 2 share) لتوليد مشاركتين سريتين. أثناء عملية التضمين ، يتم تقسيم الصورة غطاء RGB بحجم (512 × 512) إلى ثلاث طبقات (الأحمر والأخضر والأزرق). يتم تحويل الطبقة الزرقاء باستخدام التحويل Shearlet المتقطع للحصول على معاملاتها. يتم تضمين المشاركة السرية الأولى في معاملات الطبقة الزرقاء المحولة للحصول على صورة الاخفاء. في عملية الاستخراج ، يتم استخراج المشاركة السرية الأولى من معاملات الطبقة الزرقاء لصورة الاخفاء وثم يتم تطبيق عملية XOR عليها مع المشاركة السرية الثانية لإنشاء الشعار السري الأصلي. وفقًا للنتائج التجريبية ، فإن الطريقة المقترحة قد حققت افضل نسبة من عدم الوضوح لصورة الاخفاء بقدرة الحمولة الصافية تساوي (1 bpp). أصبح الشعار السري أكثر أمانًا باستخدام التشفير المرئي (2 out 2 share)  والمشاركة السرية الثانية كمفتاح خاص ايضاً.  Recently, the internet has made the users able to transmit the digital media in the easiest manner. In spite of this facility of the internet, this may lead to several threats that are concerned with confidentiality of transferred media contents such as media authentication and integrity verification. For these reasons, data hiding methods and cryptography are used to protect the contents of digital media. In this paper, an enhanced method of image steganography combined with visual cryptography has been proposed. A secret logo (binary image) of size (128x128) is encrypted by applying (2 out 2 share) visual cryptography on it to generate two secret share. During the embedding process, a cover red, green, and blue (RGB) image of size (512x512) is divided into three layers (red, green and blue). The blue layer is transformed using Discrete Shearlet Transform (DST) to obtain its coefficients. The first secret share is embedded at the coefficients of transformed blue layer to obtain a stego image. At extraction process, the first secret share is extracted from the coefficients of blue layer of the stego image and XORed with the second secret share to generate the original secret logo. According to the experimental results, the proposed method is achieved better imperceptibility for the stego image with the payload capacity equal to (1 bpp). In addition, the secret logo becomes more secured using (2 out 2 share) visual cryptography and the second secret share as a private key

Energy balance in Spectral Filter Array camera design

Multispectral imaging permits to capture more spectral information on object surface properties than color imaging. This is useful for machine vision applications. Transmittance spectral filter arrays combined with a solid state sensor form an emerging technology used for snapshot acquisition. In spectral filter arrays technology, the sensitivities of the camera have critical consequences, not only on applications, but also in the viability of the system. We discuss how to balance the energy of each channel in single exposure multispectral imaging

Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

Multispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields

Recovering 3D Shape with Absolute Size from Endoscope Images Using RBF Neural Network

Medical diagnosis judges the status of polyp from the size and the 3D shape of the polyp from its medical endoscope image. However the medical doctor judges the status empirically from the endoscope image and more accurate 3D shape recovery from its 2D image has been demanded to support this judgment. As a method to recover 3D shape with high speed, VBW (Vogel-Breuß-Weickert) model is proposed to recover 3D shape under the condition of point light source illumination and perspective projection. However, VBW model recovers the relative shape but there is a problem that the shape cannot be recovered with the exact size. Here, shape modification is introduced to recover the exact shape with modification from that with VBW model. RBF-NN is introduced for the mapping between input and output. Input is given as the output of gradient parameters of VBW model for the generated sphere. Output is given as the true gradient parameters of true values of the generated sphere. Learning mapping with NN can modify the gradient and the depth can be recovered according to the modified gradient parameters. Performance of the proposed approach is confirmed via computer simulation and real experiment

Structure-aware image denoising, super-resolution, and enhancement methods

Denoising, super-resolution and structure enhancement are classical image processing applications. The motive behind their existence is to aid our visual analysis of raw digital images. Despite tremendous progress in these fields, certain difficult problems are still open to research. For example, denoising and super-resolution techniques which possess all the following properties, are very scarce: They must preserve critical structures like corners, should be robust to the type of noise distribution, avoid undesirable artefacts, and also be fast. The area of structure enhancement also has an unresolved issue: Very little efforts have been put into designing models that can tackle anisotropic deformations in the image acquisition process. In this thesis, we design novel methods in the form of partial differential equations, patch-based approaches and variational models to overcome the aforementioned obstacles. In most cases, our methods outperform the existing approaches in both quality and speed, despite being applicable to a broader range of practical situations.Entrauschen, Superresolution und Strukturverbesserung sind klassische Anwendungen der Bildverarbeitung. Ihre Existenz bedingt sich in dem Bestreben, die visuelle Begutachtung digitaler Bildrohdaten zu unterstützen. Trotz erheblicher Fortschritte in diesen Feldern bedürfen bestimmte schwierige Probleme noch weiterer Forschung. So sind beispielsweise Entrauschungsund Superresolutionsverfahren, welche alle der folgenden Eingenschaften besitzen, sehr selten: die Erhaltung wichtiger Strukturen wie Ecken, Robustheit bezüglich der Rauschverteilung, Vermeidung unerwünschter Artefakte und niedrige Laufzeit. Auch im Gebiet der Strukturverbesserung liegt ein ungelöstes Problem vor: Bisher wurde nur sehr wenig Forschungsaufwand in die Entwicklung von Modellen investieret, welche anisotrope Deformationen in bildgebenden Verfahren bewältigen können. In dieser Arbeit entwerfen wir neue Methoden in Form von partiellen Differentialgleichungen, patch-basierten Ansätzen und Variationsmodellen um die oben erwähnten Hindernisse zu überwinden. In den meisten Fällen übertreffen unsere Methoden nicht nur qualitativ die bisher verwendeten Ansätze, sondern lösen die gestellten Aufgaben auch schneller. Zudem decken wir mit unseren Modellen einen breiteren Bereich praktischer Fragestellungen ab