We describe the system architecture and the programming environment of the Pixel Machine - a parallel image computer for 2D and 3D image synthesis and analysis. The architecture of the computer is based on an array of asynchronous MIMD nodes with a parallel access to a large frame buffer. The system consists of a pipeline of pipe nodes which execute sequential algorithms and an array of m x n pixel nodes which execute parallel algorithms. A pixel node accesses every m-th pixel on every n-th scan line of a distributed frame buffer. Each processing node is based on a high-speed, floating-point programmable processor. The programmability of the computer allows all algorithms to be implemented in software. A set of mapping functions transfers image algorithms written for conventional single-processor computers to algorithms which execute in the pixel nodes and access the distributed frame buffer. The ability to use floating-point computations in pixel operations, such as antialiasing, ray tracing, and filtering, allows high-quality image generation and processing. The image computer provides up to 820 megaflops of peak processing power and 48 megabytes of memory for data-visualization applications.

We describe the system architecture and the programming environment of the Pixel Machine - a parallel image computer with a distributed frame buffer.The architecture of the computer is based on an array of asynchronous MIMD nodes with parallel access to a large frame buffer. The machine consists of a pipeline of pipe nodes which execute sequential algorithms and an array of m × n pixel nodes which execute parallel algorithms. A pixel node directly accesses every m-th pixel on every n-th scan line of an interleaved frame buffer. Each processing node is based on a high-speed, floating-point programmable processor.The programmability of the computer allows all algorithms to be implemented in software. We present the mappings of a number of geometry and image-computing algorithms onto the machine and analyze their performance.

FRAMES is a set of flexible software tools, developed for the UNIX programming environment, that can be used to generate images and animation of 3D scenes. In FRAMES, each stage of the image-rendering pipeline is assigned to a UNIX System filter. The following is a typical FRAMES pipe sequence where each filter performs a task implied by its name:cat scene.frm|euclid|mover|shade|camera|abufFRAMES was designed to be easy to use, to permit flexible experimentation with new ideas in image rendering and geometric modeling, to allow distribution of different parts of the rendering pipeline to different processors, and to specify images in a common format for display on a variety of devices.The user communicates with FRAMES via a command language. This language is extended whenever a software developer needs to incorporate a new idea into the system by adding new commands. Data flowing through the pipeline is modified by a collection of filter programs and passed through the pipe in text or binary format.The modular and pipe-based nature of FRAMES allows for multi/parallel processor implementations and device independence. FRAMES has generated images on a local-area network of minicomputers (each filter runs on a different processor) and on a 64-processor hypercube machine (one filter runs on 64 processors). Applications of FRAMES have ranged from reconstruction of neurons from serial sections to rendering of antialiased octree objects with subpixel detail.

This paper describes a procedure for modeling motion blur in computer-generated images. Motion blur in photography or cinematography is caused by the motion of objects during the finite exposure time the camera shutter remains open to record the image on film. In computer graphics, the simulation of motion blur is useful both in animated sequences where the blurring tends to remove temporal aliasing effects and in static images where it portrays the illusion of speed or movement among the objects in the scene.

a LensThis paper extends the traditional pinhole camera projection geometry used in computer graphics to a more realistic camera model which approximates the effects of a lens and an aperture function of an actual camera.This model allows the generation of synthetic images which have a depth of field and can be focused on an arbitrary plane; it also permits selective modeling of certain optical characteristics of a lens.The model can be expanded to include motion blur and special-effect filters.These capabilities provide additional tools for highlighting important areas of a scene and for portraying certain physical characteristics of an object in an image.

This paper extends the traditional pin-hole camera projection geometry, used in computer graphics, to a more realistic camera model which approximates the effects of a lens and an aperture function of an actual camera. This model allows the generation of synthetic images which have a depth of field, can be focused on an arbitrary plane, and also permits selective modeling of certain optical characteristics of a lens. The model can be expanded to include motion blur and special effect filters. These capabilities provide additional tools for highlighting important areas of a scene and for portraying certain physical characteristics of an object in an image.