Firas Hassan

A real-time implementation of gradient domain high dynamic range compression using a local Poisson solver

This paper presents a real-time hardware implementation of a gradient domain dynamic range compression algorithm for high dynamic range (HDR) images. This technique works by calculating the gradients of the HDR image, manipulating those gradients, and reconstructing an output low dynamic range image that corresponds to the manipulated gradients. Reconstruction involves solving the Poisson equation. We propose a Poisson solver that utilizes only local information around each pixel along with special boundary conditions, and requires a small and fixed amount of hardware for any image size, with no need to buffer the entire image. The hardware implementation is described in VHDL and synthesized for a field programmable gate array (FPGA) device. The maximum operating frequency achieved is fast enough to process high dynamic range videos with one megapixel per frame at a rate of about 100 frames per second. The hardware is tested on standard HDR images from the Debevec library. The output images produced have good visual quality.

A modified approximation of 2D Gaussian smoothing filters for fixed-point platforms

Gaussian smoothing filters are commonly used in various image processing applications to reduce the noise level in an image. The filters are particularly popular in edge detection algorithms because of their ability to smooth false edges and improve the edge detection performance. When implemented on a fixed-point computational platform, the filter coefficients are rounded and the implemented filter becomes a rounded approximation of the original one. In those implementations, system designers must balance between signal integrity and the hardware size they can afford in a particular design. In this work, we suggest a new “modified” method to approximate the coefficients of a 2D Gaussian filter. When implemented on a Field Programmable Gate Array (FPGA), the modified approximation filter is shown to generally deliver higher signal quality than its traditional “rounded” counterpart without any increase in the required resources.

Symmetric synchronous stream encryption using images

In this paper, a symmetric synchronous stream encryption technique is suggested. The proposed technique utilizes a selected block from the parity bit plane of a public image as a nonlinear function to confuse the relation between the ciphered bits and the key stream. Using the proposed technique, any sort of message like text or image can be encrypted as well as decrypted bit by bit. Simulation results showed that ciphered gray scale images have flat histogram with entropy almost equal to eight and a correlation between pixels in all directions which is almost equal to zero. The technique is highly sensitive to any change in the starting pixel of the selected block or the initial condition of the pseudo-random generator.

Recursive implementation of exponential linear phase FIR filters

A family of exponential linear phase FIR filters that can be recursively implemented is proposed in this work. The advantage of this family is that the hardware implementation requires a fixed number of scalar multiplication and addition/subtraction operations, regardless of the filter order. Part of the arithmetic operations used in the implementation of these filters mandates exact computations, without any truncation or rounding. The paper includes a detailed discussion of the bit-width requirements of these operations. The proposed implementation is described in hardware description language and simulated using ModelSim. The simulation results show that, when done properly, the recursive implementation successfully achieved a linear phase response.

Exploiting redundancy to solve the Poisson equation using local information

This paper proposes a novel method of solving the Poisson equation used in image processing techniques that are based on computations in the gradient domain. The Poisson equation is used to perform an inverse gradient transform; it back-solves to find an image that is closest to having a particular gradient. The traditional methods for back-solving require access to the entire gradient-domain image; in a real-time embedded implementation, this implies high hardware complexity, large latency, and large memory buffers. We propose a method that produces high quality results visually and is based on a small sliding window with specially chosen boundary conditions. The method has been simulated as a proof of concept, and should result in much faster and smaller digital hardware than traditional approaches.

Resilient distributed parameter estimation in heterogeneous time-varying networks

In this paper, we study a lightweight algorithm for distributed parameter estimation in a heterogeneous network in the presence of adversary nodes. All nodes interact under a local broadcast model of communication in a time-varying network comprised of many inexpensive normal nodes, along with several more expensive, reliable nodes. Either the normal or reliable nodes may be tampered with and overtaken by an adversary, thus becoming an adversary node. The reliable nodes have an accurate estimate of their true parameters, whereas the inexpensive normal nodes communicate and take difference measurements with neighbors in the network in order to better estimate their parameters. The normal nodes are unsure, a priori, about which of their neighbors are normal, reliable, or adversary nodes. However, by sharing information on their local estimates with neighbors, we prove that the resilient iterative distributed estimation (RIDE) algorithm, which utilizes redundancy by removing extreme information, is able to drive the local estimates to their true parameters as long as each normal node is able to interact with a sufficient number of reliable nodes often enough and is not directly influenced by too many adversary nodes.

Recursive implementation of gaussian filters with switching and reset hardware

This paper suggests the use of linear programming and curve fitting to approximate Gaussian filters with a combination of recursive linear-phase exponential filters. The switching and reset method is used to create a stable implementation of an otherwise unstable pole-zero cancelation in the exponential filters. The results show that an accurate approximation of a Gaussian filter, of any order, can be recursively implemented using only 18 constant coefficient multipliers and 26 adders.

Embedding high dynamic range tone mapping in JPEG compression

A method that integrates tone mapping for high dynamic range (HDR) gray-scale images with JPEG compression is proposed. The tone mapping operator (TMO) is block-based, and structured so that the same discrete cosine transform (DCT) that is used for the JPEG compression serves to complete a major part of the tone-mapping operation. Simulations have been done on high dynamic range images from the Debevec library. Experimental results show the technique successfully tone maps and compresses simultaneously; the number of bits per pixel is reduced from 32 to an average of 0.67 by the compression, with an average PSNR of 56.3 dB for the compressed tone-mapped images compared to images that have been only tone-mapped. The output of the proposed method is an image that requires only limited storage space, and can be decompressed with a standard JPEG decoder.

Inculcating an entrepreneurial mindset in engineering education: Project approach

In a competitive global economy, it is important for engineering students to develop entrepreneurial skills that include effective collaboration and communication, persisting and learning from failure, management, and solving ambiguous problems. This paper summarizes a project that aims to instill these skills as part of an entrepreneurial mindset in engineering students. The project was implemented in an introductory electric circuits class with a mixed representation of students majoring in electrical, computer, civil, and mechanical engineering. Students were organized into groups of two or three to design a temperature sensor using a negative temperature coefficient thermistor. Students groups were provided with customer specifications and were given a month to research the problem and obtain a viable solution. The groups were required to provide evidence compiled into a written product proposal that included a bill of materials, cost analysis, circuit design and simulation, testing plan, layout of the printed circuit board and packaging schematic, delivery time, and the voltage-temperature relationship of the designed circuit. After submitting the written proposal, each group was given five minutes to pitch their proposal using a poster in an effort to convince the customer (in this case, the instructor) that their design was the best and most cost-effective solution.

A study of hardware-friendly methods for gradient domain tone mapping of high dynamic range images

A large class of techniques for image processing is based on manipulation of the gradient field of an image. These techniques have high computational complexity, due to the need to solve an inverse problem, taking the form of a Poisson equation, to find the output image that best matches a manipulated gradient field. This work studies hardware-friendly techniques, appropriate for implementation on a field-programmable gate array implementation and embeddable inside a camera, for approximating this solution. Fattal’s operator for the dynamic range compression of high dynamic range images is studied as a representative example application. A family of methods, inspired by Fattal’s operator but with significantly lower computational complexity, solves the inverse problem in a moving window of small size. In this paper, a study is conducted to understand the role that the boundary conditions and the size of the window play in the quality of the resulting output image and the size of the hardware. The impact of using single-scale and multi-scale approaches to compute the attenuation factors needed for Fattal’s operator is also considered.