Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this study, the authors consider additive spread-spectrum (SS) data embedding in transform-domain host data. Conventional additive SS embedding schemes use an equal-amplitude modulated carrier to deposit one information symbol across a group of host data coefficients which act as interference to SS signal of interest. If there is a flexibility of assigning different amplitudes across symbol bits, the probability of error can be further reduced by adaptively allocating amplitude to each symbol bit based on its own host/interference. In this study, they present a novel amplitude-adaptive SS embedding scheme. Particularly, symbol-by-symbol adaptive amplitude allocation algorithms are developed to compensate for the impact from the known interference. They aim at designing the SS embedding amplitude for each symbol adaptively in order to minimise the receiver bit-error-rate (BER) at any given distortion level. Then, optimised amplitude allocation for multi-carrier/multi-message embedding in the same host data is studied as ll. Finally, they consider the problem of amplitude optimisation for an ideal scenario where no external noise is introduced during embedding and transmission. Extensive experimental results illustrate that the proposed amplitude-adaptive SS embedding scheme can provide order-of-magnitude performance improvement over several other state-of-the-art SS embedding schemes.
['Ming Li', 'Qian Liu', 'Yanqing Guo', 'Bo Wang', 'Xiangwei Kong']
I am writing a research paper on a idea Amplitude-adaptive spread-spectrum data embedding
[{"from": "human", "value": "I am writing a research paper on a idea Amplitude-adaptive spread-spectrum data embedding"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In this study, the authors consider additive spread-spectrum (SS) data embedding in transform-domain host data. Conventional additive SS embedding schemes use an equal-amplitude modulated carrier to deposit one information symbol across a group of host data coefficients which act as interference to SS signal of interest. If there is a flexibility of assigning different amplitudes across symbol bits, the probability of error can be further reduced by adaptively allocating amplitude to each symbol bit based on its own host/interference. In this study, they present a novel amplitude-adaptive SS embedding scheme. Particularly, symbol-by-symbol adaptive amplitude allocation algorithms are developed to compensate for the impact from the known interference. They aim at designing the SS embedding amplitude for each symbol adaptively in order to minimise the receiver bit-error-rate (BER) at any given distortion level. Then, optimised amplitude allocation for multi-carrier/multi-message embedding in the same host data is studied as ll. Finally, they consider the problem of amplitude optimisation for an ideal scenario where no external noise is introduced during embedding and transmission. Extensive experimental results illustrate that the proposed amplitude-adaptive SS embedding scheme can provide order-of-magnitude performance improvement over several other state-of-the-art SS embedding schemes."}]