Search Results (2)

High dynamic range (HDR) imaging aims to overcome the limited dynamic range of traditional imaging systems and achieve effective restoration of the brightness and color of the real world. In recent years, single-image HDR (SI-HDR) reconstruction technology has become a research hotspot due to its simple acquisition process and applicability to dynamic scenes. This paper proposes an improved SI-HDR reconstruction method based on HDRUNet, which systematically integrates channel, spatial attention mechanism, brightness expansion, and color-enhancement branches, and constructs an adaptive multi-component loss function. This effectively enhances the detail restoration in extreme exposure areas and improves the overall color expressiveness. Experiments on public datasets such as NTIRE 2021, VDS, and HDR-Eye show that the proposed method outperforms the mainstream SI-HDR methods in terms of PSNR, SSIM, and VDP evaluation metrics. It performs particularly well in complex scenarios, demonstrating greater robustness and generalization ability. Full article

This paper presents an optimal weighted modulus (OWM) algorithm able to conceal secret messages in a high dynamic range image encoded via the RGBE format, consisting of the red, green, blue, and exponent channels. In contrast to current state-of-the-art schemes, which mainly employ limited and vulnerable homogeneous representations, our OWM scheme exploits four channels and an embedding weight to conceal secret messages, thereby offering more embedding capacities and undetectability against steganalytic tools. To reduce the impact on the luminance variation, we confine the maximal change incurred in the exponent channel when embedding secret messages. In addition, we propose an SEC scheme to eliminate the pixel saturation problem, even though a pixel contains values close to the boundary extreme. As a result, the stego images produced not only exhibit high quality but also comply with the RGBE encoding format, making them able to resist malicious steganalytic detection. The experimental results show that our scheme offers larger embedding rates, between 2.8074 and 5.7549 bits per pixel, and the average PSNR value for twelve tone-mapped images is over 48 dB. In addition, the HDR VDP 3.0 metric demonstrates the high fidelity of stego HDR images, where the average Q value is close to the upper bound of 10.0. Our scheme can defeat RS steganalytic attacks and resist image compatibility attacks. A comparison result confirms that our scheme outperforms six current state-of-the-art schemes. Full article