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Histopathology for tumor margin assessment is time‐consuming and expensive. High‐resolution full‐field optical coherence tomography (FF‐OCT) images fresh tissues rapidly at cellular resolution and potentially facilitates evaluation. Here, we define FF‐OCT features of normal and neoplastic skin lesions in fresh ex vivo tissues and assess its diagnostic accuracy for malignancies. For this, normal and neoplastic tissues were obtained from Mohs surgery, imaged using FF‐OCT, and their features were described. Two expert OCT readers conducted a blinded analysis to evaluate their diagnostic accuracies, using histopathology as the ground truth. A convolutional neural network was built to distinguish and outline normal structures and tumors. Of the 113 tissues imaged, 95 (84%) had a tumor (75 basal cell carcinomas [BCCs] and 17 squamous cell carcinomas [SCCs]). The average reader diagnostic accuracy was 88.1%, with a sensitivity of 93.7%, and a specificity of 58.3%. The artificial intelligence (AI) model achieved a diagnostic accuracy of 87.6 ± 5.9%, sensitivity of 93.2 ± 2.1%, and specificity of 81.2 ± 9.2%. A mean intersection‐over‐union of 60.3 ± 10.1% was achieved when delineating the nodular BCC from normal structures. Limitation of the study was the small sample size for all tumors, especially SCCs. However, based on our preliminary results, we envision FF‐OCT to rapidly image fresh tissues, facilitating surgical margin assessment. AI algorithms can aid in automated tumor detection, enabling widespread adoption of this technique. [ABSTRACT FROM AUTHOR]

One common way to extend the battery life of a portable device is to reduce the LCD backlight intensity. In contrast to previous approaches that minimize the power consumption by adjusting the backlight intensity frame by frame to reach a specified image quality, the proposed method optimizes the image quality for a given backlight intensity. Image is enhanced by performing brightness compensation and local contrast enhancement. For brightness compensation, global image statistics and backlight level are considered to maintain the overall brightness of the image. For contrast enhancement, the local contrast property of human visual system (HVS) is exploited to enhance the local image details. In addition, a brightness prediction scheme is proposed to speed up the algorithm for display of video sequences. Experimental results are presented to show the performance of the algorithm. Index Terms--Contrast, image enhancement, LCD backlight, power management.

This paper presents a stochastic estimation approach to adaptive interpolation of color filter array. It models an image as a 2-D locally stationary Gaussian process and achieves robustness against aliasing by employing an edge-sensitive weighting policy based on the stochastic characteristics of uniformly oriented edge indicators. Experimental results show that the algorithm can effectively eliminate the occurrence of perceptible artifact. Performance comparison in terms of peak signal-to-noise ratio and mean square error is provided to demonstrate the superiority of the proposed algorithm. Index Terms--Color filter array (CFA), color interpolation, demosaicing, edge detection, edge-sensitive weighting.

In this work, we develop a constant-quality rate control algorithm for a surveillance system which consists of one 'base encoder' that encodes a down-sampled full-view version of the input video sequence, and one 'region of interest (ROI) encoder' that encodes the region of interest of the input video at the original resolution. Exploiting the inter-relationship between these two independent encoders, the algorithm allocates the bits for the ROI encoder according to the distortion obtained from the corresponding region in the base encoder. Simulation results show that the proposed algorithm can achieve significant reduction in the image quality variation. Compared to the rate control algorithm in JM 8.4, the overall quality is improved and the bit rate is saved. Index Terms--Bit allocation, H.264/AVC, rate control, surveillance, video coding.

This paper presents three novel schemes for integrating digital stabilizer with video codec of a digital video camera, each designed for a different application scenario. Scheme 1 confines the global motion estimation (ME) to within a small background region determined by clustering the motion vectors (MVs) generated by the video encoder. Scheme 2 performs the main ME task at the digital stabilizer and sends the resulting motion vectors to the video encoder, where the motion vectors are further refined to subpixel accuracy. Scheme 3, which is applied on the decoder side, acquires the motion information directly from the video decoder to perform digital stabilization. These integration schemes achieve computational efficiency without affecting the performance of video coding and digital stabilization. Index Terms--Digital video camera, digital video stabilization, global motion estimation (ME), ME, video coding.

The mismatch between a spatial-domain encoder and a transform-domain decoder due to rounding can cause serious video quality degradation after a series of inter-coded frames. The mismatch is rooted on the fact that rounding is a nonlinear operation, and hence its equivalent in the transform domain does not exist. We analyze the mathematical property of the rounding operation and propose a practical solution that provides an optimal approximation of the rounding operation in the transform-domain. The proposed solution is able to reduce the mismatch and preserve image quality. Experimental results are shown to demonstrate the effectiveness of the solution. Index Terms--Discrete cosine transform (DCT), motion compensation, rounding, transcoding, transform domain.