Accurate and Rapid Auto-Focus Methods Based on Image Quality Assessment for Telescope Observation

Aiming at improving the speed and accuracy of auto-focus for telescope observation, algorithms for image estimation and auto-focus were investigated and are discussed in this article. Based on the image quality assessment, the auto-focusing process of the telescope system is realized by using the mountain-climb search method. Several evaluation functions were tested in different scenarios. It is demonstrated that the Tenengrad image estimation function (IEF) is suitable for an instant and accurate auto-focus process of the telescope. Furthermore, we implemented sampling and dynamic adaptive focusing window (ES-DAFW) methods with the Tenengrad IEF to enhance the sensitivity and accuracy of the auto-focus process. The experimental results showed that our ES-DATW method can provide more accurate results in less time for the auto-focus process compared to the conventional approaches, especially for a sparse image. These results promise significant applications to the auto-focusing of other telescopes with image quality assessment.

Payload location for JPEG image steganography based on co-frequency sub-image filtering

In digital steganography, due to difficulties estimating the JPEG cover image, it is still very hard to accurately locate the hidden message embedded in a JPEG image. Therefore, this study proposes a payload location method for a category of pseudo-random scrambled JPEG image steganography. In order to estimate the quantized discrete cosine transform coefficients in the cover JPEG image, a cover JPEG image estimation method is proposed based on co-frequency sub-image filtering. The proposed payload location method defines a general residual, uses the estimated cover JPEG image to compute the residuals, and then employs the mean residuals of multiple stego images embedded along the same path to distinguish the stego positions. The proposed cover JPEG image estimation method constructs 64 co-frequency sub-images, and then filters the sub-image to estimate the cover JPEG image. Finally, using these methods, payload location algorithms are designed for two common JPEG image steganography algorithms: JSteg and F5. Experimental results show that the proposed location algorithms can effectively locate the stego positions in both JSteg and F5 steganography when the investigator possesses multiple stego images embedded along the same path. In addition, the location results can also be used to recover the steganography key to extract the embedded secret messages.