Biomedical subjects

Edmund Y Lam

Publications and source records attributed to Edmund Y Lam.

3 recordsLinked to original sources

PubMed2007

Binary image restoration by positive semidefinite programming.

We report an optimization approach to restore degraded binary images by using positive semidefinite programming when the point spread function (PSF) is known. The approach takes advantage of the combinatorial nature of the problem, considering not only local similarity and spatial context but also the relationship between individual pixel values and the PSF. Numerical experiments confirm the superiority of the approach.

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PubMed2003

Noise in superresolution reconstruction.

Recently there has been a significant interest in reconstructing a high-resolution (HR) image based on a set of low-resolution (LR) images with relative displacement. These images are typically undersampled with respect to the image spectrum of a HR image. I show that, although ideally a resolution increase of N times is possible with N LR images, in a practical system noise is a limiting factor that increases substantially as we approach this theoretical superresolution limit. For one dimension and a special case with two LR images, I present an analytical result of the noise amplification as a function of their displacement. This is defined as a condition number of the superresolution system, with the associated definitions of a well-conditioned and ill-conditioned superresolution reconstruction system.

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PubMed2002

Digital restoration of defocused images in the wavelet domain.

Many cameras nowadays are equipped with an autofocus mechanism that attempts to take pictures at the best possible focus. However, there are situations in which the pictures are still out of focus, such as when the photographer has mistakenly focused at a wrong position or when the focusing region consists of objects of different depths and therefore confuses the autofocus system. With a digital camera, we can attempt to use digital image-restoration techniques to bring the pictures back into focus. We design an algorithm that restores the image by digitally enhancing the corresponding frequency bands. We employ the restoration in the wavelet domain so that this restoration scheme can be compliant with JPEG 2000, which is positioned to succeed JPEG as the next image-compression standard and has the potential to be widely adopted by the digital photography industry owing to its many advanced features.

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