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This paper proposes a new way of managing the cache by exploiting the difference of behavior in the memory system between read-only data and read-write data. A division of the existing cache-based memory hierarchy is proposed in order to create a dedicated data path for read-only data. In order to justify this approach, an analysis performed on a set of benchmarks shows that read-only data count for...
This paper proposes a new way of managing the cache by exploiting the difference of behavior in the memory system between read-only data and read-write data. A division of the existing cache-based memory hierarchy is proposed in order to create a dedicated data path for read-only data. In order to justify this approach, an analysis performed on a set of benchmarks shows that read-only data count for...
In this work, we study the performance benefits of using asynchronous data transfers in OpenCL programs executing on media processors. Asynchronous data transfers are typically implemented by use of Direct Memory Access (DMA) engines that can be programmed to transfer data from one memory location to another. Asynchronous transfers can free up processing cores from managing data transfers and having...
In this paper, we introduce a new public image dataset for Devanagari script: Devanagari Handwritten Character Dataset (DHCD). Our dataset consists of 92 thousand images of 46 different classes of characters of Devanagari script segmented from handwritten documents. We also explore the challenges in recognition of Devanagari characters. Along with the dataset, we also propose a deep learning architecture...
We are publishing an open source library to facilitate the use of three key image processing technologies (GDAL, OpenCV, CUDA) for scalable, high performance geospatial data processing. Herein, we present two computationally demanding algorithms for geospatial data processing which are commonly used for complex structural analysis of imagery. We show that processing time can be reduced by 98.1% and...
Recently, the OpenCL hardware-software co-design methodology has gained traction in realizing effective parallel architecture designs in heterogeneous FPGA platforms. In fact, the portability of OpenCL on hardware ready platforms such as GPU or multicore CPU enables ease of design verification. This is true especially for parallel algorithms before implementing them using cumbersome HDL-based RTL...
Digital fundus photographs are often used to provide clinical diagnostic information about several pathologies such as diabetes, glaucoma, macular degeneration and vascular and neurologic disorders. To allow a precise analysis, digital fundus image quality should be assessed to evaluate if minimum requirements are present. Focus is one of the causes of low image quality. This paper describes a method...
Embedded image processing systems have many challenges, due to large computational requirements and other physical, power, and environmental constraints. However recent contemporary mobile devices include a graphical processing unit (GPU) in order to offer better use interface in terms of graphics. Some of these embedded GPUs also support OpenCL which allows the use of computation capacity of embedded...
In this paper, a straightforward and effective method for image upsizing is presented; upsizing is considered to be an essential operation in image processing. The Wiener filtering method is a well-known optimal framework for signal prediction, which provides information of original and degraded signals. In image upsizing, the Wiener filtering framework is not valid because of the missing information...
Programming accelerators such as GPUs withlow-level APIs and languages such as OpenCL and CUDAis difficult, error-prone, and not performance-portable. Au-tomatic parallelization and domain specific languages (DSLs)have been proposed to hide complexity and regain performanceportability. We present P ENCIL, a rigorously-defined subset ofGNU C99 -- enriched with additional language constructs -- that...
Image processing algorithms are widely used in the automotive field for ADAS (Advanced Driver Assistance System) purposes. To embed these algorithms, semiconductor companies offer heterogeneous architectures which are composed of different processing units, often with massively parallel computing unit. However, embedding complex algorithms on these So Cs (System on Chip) remains a difficult task due...
This paper proposes a method for segmentation of images containing both textual and graphical data. The method uses wavelet transformation to build the feature vector and a pattern recognition technique to classify areas of a document image. Values of wavelet coefficients distribution histogram of the source images sliding window serve as elements of a feature vector. For recognition of document area...
Tiling is a key aspect of the design of embedded image processing applications, due to local memory constraints. To maximize system performance, the designer must select a suitable tile size that balances data transfers and computation. In this work, we present a method for optimal 2D image tile sizing using constraint programming. Unlike previous methods, ours accurately models DMA data transfer...
ADAS (Advanced Driver Assistance Systems) algorithms increasingly use heavy image processing operations. To embed this type of algorithms, semiconductor companies offer many heterogeneous architectures. These SoCs (System on Chip) are composed of different processing units, with different capabilities, and often with massively parallel computing unit. Due to the complexity of these SoCs, predicting...
Interferometric Synthetic Aperture Radar (InSAR) is a remote sensing technology used for estimating displacement of the earth's surface. Phase unwrapping is the most important step in InSAR processing and relies on successful selection of points that appear stable across a set of satellite images taken over time. This paper presents a new algorithm for selecting these points, a problem known as persistent...
Current tools for High-Level Synthesis (HLS) excel at exploiting Instruction-Level Parallelism (ILP), the support for Data-Level Parallelism (DLP), one of the key advantages of Field Programmable Gate Arrays (FPGAs), is in contrast very limited. This work examines the exploitation of DLP on FPGAs using code generation for C-based HLS of image filters and streaming pipelines, consisting of point and...
2D Convolution is the most convenient method to analyze digital image and video processing and has a variety of digital image processing applications such as edge detection, image enhancement, image segmentation, smoothing or blurring an image and can be applied to video processing on the basis of frame by frame for motion detection. Though the computational complexity of 2D convolution is comparatively...
In this paper, we generalize the notion of Kantorovich-type sampling operators using the Fejér-type singular integral. By means of these operators we are able to reconstruct signals (functions) which are not necessarily continuous. Moreover, our generalization allows us to take the measurement error into account. The goal of this paper is to estimate the rate of approximation by the above operators...
This 1-Page Demonstration paper is included in the track “Multimedia Systems and Applications”. The work has been already published in [1] and [2]. The main idea of the demonstration is to show how the Virtual Architecture ARTICo3 works within a high performance wireless sensor node called HiReCookie. The selected demo includes an image processing application with several filters running as different...
In recent years, due to a higher demand for portable devices, which provide restricted amounts of processing capacity and battery power, the need for energy and time efficient hard and software solutions has increased. Preliminary estimations of time and energy consumption can thus be valuable to improve implementations and design decisions. To this end, this paper presents a method to estimate the...
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