Modular Human-in-the-loop Design Framework Based on Human Factors

Human-in-the-loop design framework introduced in this dissertation utilizes Digital Human Modeling (DHM) to incorporate Human Factors Engineering (HFE) design principles early in design process. It embodies scientific methods (e.g., mathematics) and artistic approaches (e.g., visualization) to assess human well-being and overall system performance. This framework focuses not only on ergonomics assessments but also actual design process including, but not limited to, concept development, structural integrity and digital prototyping. It addresses to three major limitations found in HFE literature and practices

Resolution enhancement of imagestakenby mobile phonecamera

Carey and co-researchers have estimated a super-resolution technique DA SR (Demirel-Anbarjafari Super Resolution), based on interpolation of the high frequency sub-band images obtained by discrete wavelet transform (DWT). Their estimation was carried out by investigating the evolution of wavelet transform extrema among the same type of subbands. Edges identified by an edge detection algorithm in lower frequency subbands were used to prepare a model for estimating edges in higher frequency subbands; and only the coefficients with significant values were estimated as the evolution of the wavelet coefficients. Finally, interpolated high-frequency sub-band images and the interpolated input image are combined by using IDWT to achieve a high resolution output image. The technique has been implemented in Java language in order to be installed on the mobile phones. The DA SR technique has been tested on well-known benchmark images

Resolution enhancement of video sequences by using discrete wavelet transform and illumination compensation

This research paper proposes a new technique for video resolution enhancement that employees an illumination compensation procedure before the registration process. After the illumination compensation process, the respective frames are registered using the Irani and Peleg technique. In parallel, the corresponding frame is decomposed into high-frequency (low-high, high-low, and high-high) and low-frequency (low-low) subbands using discrete wavelet transform (DWT). The high-frequency subbands are superresolved using bicubic interpolation. Afterwards, the interpolated high-frequency subbands and superresolved low-frequency subband obtained by registration are used to construct the high-resolution frame using inverse DWT. The superiority of the proposed resolution enhancement method over well-known video superresolution techniques is shown with quantitative experimental results. For the Akiyo video sequence, there are improvements of 2.26 dB when compared to the average peak signal-to-noise ratio obtained by the state-of-the-art resolution technique proposed by Vandewalle