Effective solution for underwater image enhancement.

Degradation of underwater images severely limits people to exploring and understanding underwater world, which has become a fundamental but vital issue needing to be addressed in underwater optics. In this paper, we develop an effective solution for underwater image enhancement. We first employ an adaptive-adjusted artificial multi-exposure fusion (A-AMEF) and a parameter adaptive-adjusted local color correction (PAL-CC) to generate a contrast-enhanced version and a color-corrected version from the input respectively.

[Study on Electroencephalogram Recognition Framework by Common Spatial Pattern and Fuzzy Fusion].

Common spatial pattern (CSP) is a very popular method for spatial filtering to extract the features from electroencephalogram (EEG) signals, but it may cause serious over-fitting issue. In this paper, after the extraction and recognition of feature, we present a new way in which the recognition results are fused to overcome the over-fitting and improve recognition accuracy. And then a new framework for EEG recognition is proposed by using CSP to extract features from EEG signals, using linear discriminant analysis (LDA) classifiers to identify the user's mental state from such features, and using Choquet fuzzy integral to fuse classifiers results.