Number Of Gray-scale Levels Research Articles

Performance of complex visual tasks using simulated prosthetic vision via augmented-reality glasses.

Photovoltaic subretinal prosthesis is designed for restoration of central vision in patients with age-related macular degeneration (AMD). We investigated the utility of prosthetic central vision for complex visual tasks using augmented-reality (AR) glasses simulating reduced acuity, contrast, and visual field. AR glasses with blocked central 20° of visual field included an integrated video camera and software which adjusts the image quality according to three user-defined parameters: resolution, corresponding to the equivalent pixel size of an implant; field of view, corresponding to the implant size; and number of grayscale levels. The real-time processed video was streamed on a screen in front of the right eye. Nineteen healthy participants were recruited to complete visual tasks including vision charts, sentence reading, and face recognition. With vision charts, letter acuity exceeded the pixel-sampling limit by 0.2 logMAR. Reading speed decreased with increasing pixel size and with reduced field of view (7°–12°). In the face recognition task (four-way forced choice, 5° angular size) participants identified faces at >75% accuracy, even with 100 μm pixels and only two grayscale levels. With 60 μm pixels and eight grayscale levels, the accuracy exceeded 97%. Subjects with simulated prosthetic vision performed slightly better than the sampling limit on the letter acuity tasks, and were highly accurate at recognizing faces, even with 100 μm/pixel resolution. These results indicate feasibility of reading and face recognition using prosthetic central vision even with 100 μm pixels, and performance improves further with smaller pixels.

PDE-BASED HISTOGRAM MODIFICATION WITH EMBEDDED MORPHOLOGICAL PROCESSING OF THE LEVEL-SETS

This paper describes parallel histogram modification techniques with embedded morphological preprocessing methods within the CNN-UM framework. The procedure is formulated in terms of nonlinear partial differential equations (PDE) and approximated through finite differences in space, resulting in coupled nonlinear ordinary differential equations (ODE). The I/O mapping of the system (containing both local and global couplings) can be calculated by a complex analogic (analog and logic) algorithm executed on a stored program nonlinear array processor, called the cellular nonlinear network universal machine (CNN-UM3). We describe and illustrate how the implementation of the algorithm results in an adaptive multi-thresholding scheme when histogram modification is combined with embedded morphological processing at a finite (low) number of gray-scale levels. This has obvious advantages if the further processing steps are segmentation and/or recognition. Experimental results processing real-life and echocardiography images are measured on different hardware/software platforms, including a 64 × 64 CNN-UM chip (ACE4k6,17).

副尺視力に基づく画像解像度と階調の相乗効果の一検討とマルチ画面の位置合わせ用信号への適用

We studied the synergism of resolution and gray-scale levels in image recognition in relation to the precise phase detection in vernier acuity. Humans who have a 1.0 visual acuity candetect 1.0 minute-size (1/60 degree) objects. Video systems are designed based on this data. On the other hand, it has been reported that human can detect an approximately 2.0-second (2/60/60 degree) phase shifts. We found that precise position detection is possible with a low resolution detector if the number of gray-scale levels is sufficient. We applied this principle to the position adjustment on a multi-screen display system.