Randon and Ridgelet Transformation Applicaton in Image Digital Watermark

Propose a digital watermark algorithm that can be resisted geometric attack, in order to enhance the capacity to resist attacks such as rotation, use the 0° angle Randon transformation as the reference vector, estimate and correct the rotation transformation of the carrier image, recover the watermark synchronization. when watermark is embedded, perform wavelet transform on original image and blocked the LF sub-band, perform the Ridgelet transformation on each block; change two-value watermark to one-dimension, embedded the watermark bit into the Maximum energy direction of Ridgelet. The simulation results show that the algorithm can effective resist various attacks such as noise, filtering, compression, rotation, shearing and scaling etc, and the ability of resist various attacks is robust.

Statistically Efficient Estimation Using Population Coding

Coarse codes are widely used throughout the brain to encode sensory and motor variables. Methods designed to interpret these codes, such as population vector analysis, are either inefficient (the variance of the estimate is much larger than the smallest possible variance) or biologically implausible, like maximum likelihood. Moreover, these methods attempt to compute a scalar or vector estimate of the encoded variable. Neurons are faced with a similar estimation problem. They must read out the responses of the presynaptic neurons, but, by contrast, they typically encode the variable with a further population code rather than as a scalar. We show how a nonlinear recurrent network can be used to perform estimation in a near-optimal way while keeping the estimate in a coarse code format. This work suggests that lateral connections in the cortex may be involved in cleaning up uncorrelated noise among neurons representing similar variables.