A Parallel Framework for Real-time Dehazing

Optimized contrast enhancement for real-time image and video dehazing

A fast and optimized dehazing algorithm for hazy images and videos is proposed in this work. Based on the observation that a hazy image exhibits low contrast in general, we restore the hazy image by enhancing its contrast. However, the overcompensation of the degraded contrast may truncate pixel values and cause information loss. Therefore, we formulate a cost function that consists of the cont...

Time-recursive computation and real-time parallel architectures: a framework

The time-recursive computation has been proven a particularly useful tool in real-time data compression, in transform domain adaptive filtering, and in spectrum analysis. Unlike the FFT-based ones, the time-recursive architectures require only local communication. Also, they are modular and regular, thus they are very appropriate for VLSI implementation and they allow a high degree of paralleli...

A Variational Framework for Single Image Dehazing

Images captured under adverse weather conditions, such as haze or fog, typically exhibit low contrast and faded colors, which may severely limit the visibility within the scene. Unveiling the image structure under the haze layer and recovering vivid colors out of a single image remains a challenging task, since the degradation is depth-dependent and conventional methods are unable to handle thi...

Real-Time Video Dehazing Based on Spatio-Temporal MRF

A Component Framework for Real-time Java∗

The Real-time Specification for Java (RTSJ) offers predictable memory management and scheduling required for real-time applications. However, the usage of its memory model is difficult for standard Java developers, who are accustomed to automatic memory management. Components offer the opportunity to hide the complexities of the RTSJ’s memory model, in addition to benefits such as reusability a...