BMEFIQA: Blind Quality Assessment of Multi-Exposure Fused Images Based on Several Characteristics

A multi-exposure fused (MEF) image is generated by multiple images with different exposure levels, but the transformation process will inevitably introduce various distortions. Therefore, it is worth discussing how to evaluate the visual quality of MEF images. This paper proposes a new blind quality assessment method for MEF images by considering their characteristics, and it is dubbed as BMEFIQA. More specifically, multiple features that represent different image attributes are extracted to perceive the various distortions of MEF images. Among them, structural, naturalness, and colorfulness features are utilized to describe the phenomena of structure destruction, unnatural presentation, and color distortion, respectively. All the captured features constitute a final feature vector for quality regression via random forest. Experimental results on a publicly available database show the superiority of the proposed BMEFIQA method to several blind quality assessment methods.     

Effect of Input Waveform to Vibration Speaker on Sound Quality of Electric Artificial Voice

A number of studies have been conducted on the improvement of the sound quality of electrical artificial laryngeal speech, the speech produced has been difficult to hear compared to a natural voice. For this reason, it is necessary to effectively improve the frequency characteristics of the input signal. In the present study, to improve the sound quality of vocalization using an electrical artifi- cial larynx, first, a comparison of the frequency characteristics between the real and artificial voices was conducted, and three filters that can make the frequency characteristics of the artificial voice closer to those of a real voice were generated. Then, the influence of these filters on the quality of the artificial voice was investigated via physical measurement and a subjective evaluation experiment targeted at Japanese five vowels. It was found that the intelligibility of artificial /a/ and /o/ sounds was improved, whereas little improvement was observed in the case of /i/, /u/, and /e/. The obtained results confirmed the effect of optimizing the input signal into the vibration speaker and indicated areas for further improvement.