Gray-level transformations for interactive image enhancement

A gray-level transformation method suitable for interactive image enhancement was presented. It is shown that the well-known histogram equalization approach is a special case of this method. A technique for improving the uniformity of a histogram is also developed. Experimental results which illustrate the capabilities of both algorithms are described. Two proposals for implementing gray-level transformations in a real-time interactive image enhancement system are also presented

METEOSAT studies of clouds and radiation budget

Radiation budget studies of the atmosphere/surface system from Meteosat, cloud parameter determination from space, and sea surface temperature measurements from TIROS N data are all described. This work was carried out on the interactive planetary image processing system (IPIPS), which allows interactive manipulationion of the image data in addition to the conventional computational tasks. The current hardware configuration of IPIPS is shown. The I(2)S is the principal interactive display allowing interaction via a trackball, four buttons under program control, or a touch tablet. Simple image processing operations such as contrast enhancing, pseudocoloring, histogram equalization, and multispectral combinations, can all be executed at the push of a button

Digital enhancement of flow field images

Most photographs of experimentally generated fluid flow fields have inherently poor photographic quality, specifically low contrast. Thus, there is a need to establish a process for quickly and accurately enhancing these photographs to provide improved versions for physical interpretation, analysis, and publication. A sequence of digital image processing techniques which have been demonstrated to effectively enhance such photographs is described

Balanced Quantization: An Effective and Efficient Approach to Quantized Neural Networks

Quantized Neural Networks (QNNs), which use low bitwidth numbers for representing parameters and performing computations, have been proposed to reduce the computation complexity, storage size and memory usage. In QNNs, parameters and activations are uniformly quantized, such that the multiplications and additions can be accelerated by bitwise operations. However, distributions of parameters in Neural Networks are often imbalanced, such that the uniform quantization determined from extremal values may under utilize available bitwidth. In this paper, we propose a novel quantization method that can ensure the balance of distributions of quantized values. Our method first recursively partitions the parameters by percentiles into balanced bins, and then applies uniform quantization. We also introduce computationally cheaper approximations of percentiles to reduce the computation overhead introduced. Overall, our method improves the prediction accuracies of QNNs without introducing extra computation during inference, has negligible impact on training speed, and is applicable to both Convolutional Neural Networks and Recurrent Neural Networks. Experiments on standard datasets including ImageNet and Penn Treebank confirm the effectiveness of our method. On ImageNet, the top-5 error rate of our 4-bit quantized GoogLeNet model is 12.7\%, which is superior to the state-of-the-arts of QNNs

Study of optical techniques for the Ames unitary wind tunnel: Digital image processing, part 6

A survey of digital image processing techniques and processing systems for aerodynamic images has been conducted. These images covered many types of flows and were generated by many types of flow diagnostics. These include laser vapor screens, infrared cameras, laser holographic interferometry, Schlieren, and luminescent paints. Some general digital image processing systems, imaging networks, optical sensors, and image computing chips were briefly reviewed. Possible digital imaging network systems for the Ames Unitary Wind Tunnel were explored

Color image processing and object tracking workstation

A system is described for automatic and semiautomatic tracking of objects on film or video tape which was developed to meet the needs of the microgravity combustion and fluid science experiments at NASA Lewis. The system consists of individual hardware parts working under computer control to achieve a high degree of automation. The most important hardware parts include 16 mm film projector, a lens system, a video camera, an S-VHS tapedeck, a frame grabber, and some storage and output devices. Both the projector and tapedeck have a computer interface enabling remote control. Tracking software was developed to control the overall operation. In the automatic mode, the main tracking program controls the projector or the tapedeck frame incrementation, grabs a frame, processes it, locates the edge of the objects being tracked, and stores the coordinates in a file. This process is performed repeatedly until the last frame is reached. Three representative applications are described. These applications represent typical uses and include tracking the propagation of a flame front, tracking the movement of a liquid-gas interface with extremely poor visibility, and characterizing a diffusion flame according to color and shape