In this paper, we study the restoration of images corrupted by Gaussian plus salt-and-pepper noise, and propose a l 1-l 0 minimization approach where the l 1 term is from impulse noise and the l 0 term is from the assumption that the clean image patches admit a sparse representation over certain unknown dictionary. The main algorithm contains three phases. First, we identify the outlier candidates which are likely to be corrupted by salt-and-pepper impulse noise. Second, we recover the image via dictionary learning on the free-outlier pixels. Finally, an alternating minimization algorithm is employed to solve the proposed minimization energy function, leading to an further restoration based on the recovered image in the second step. Comparative experiments are carried out to show the leading performance of the proposed method.

A novel chemiluminescence enzyme immunoassay using bacterial magnetic particles (BMPs) has been developed for highly sensitive and rapid detection of immunoglobulin G. Antibody was immobilized onto BMPs using the heterobifunctional reagents sulfosuccinimidyl 6-[3'-(2-pyridyldithio) propionamido]hexanoate (sulfo-LC-SPDP) and sulfosuccinimidyl 4-(N-maleimidomethyl)cyclohexane-1-carboxylate (sulfo-SMCC). For the highly sensitive immunoassay method using these BMPs, a good relationship was obtained between the luminescence intensity and mouse IgG concentration in the range of 1-10(5) fg/mL. Furthermore, in order to reduce assay time and to simplify operations, a rapid chemiluminescence enzyme immunoassay method has been developed. The rapid method was completed in 10 min. A linear relationship was obtained between the luminescence and mouse IgG concentration in the range of 10-1000 ng/mL.

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