“…(On the left is the original image, top two rows on the right are non-salient regions of reconstructed image, and two bottom rows on the right are salient ones. From left to right, the first row is original image, official implementation of JPEG XT profile A,B,C, the second row is Choi's method10 [10], Wei's method 21 [21], Feyiz's method 22 [22], and our proposed method, respectively. )Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Their method is suitable to preserve local contrast and has lower computational complexity. Choi et al [10] proposed a novel method that is completely different from others. They generated the residual data in the DCT domain.…”
With wider luminance range than conventional low dynamic range (LDR) images, high dynamic range (HDR) images are more consistent with human visual system (HVS). Recently, JPEG committee releases a new HDR image compression standard JPEG XT. It decomposes an input HDR image into base layer and extension layer. The base layer code stream provides JPEG (ISO/IEC 10918) backward compatibility, while the extension layer code stream helps to reconstruct the original HDR image. However, this method does not make full use of HVS, causing waste of bits on imperceptible regions to human eyes. In this paper, a visual saliency-based HDR image compression scheme is proposed. The saliency map of tone mapped HDR image is first extracted, then it is used to guide the encoding of extension layer. The compression quality is adaptive to the saliency of the coding region of the image. Extensive experimental results show that our method outperforms JPEG XT profile A, B, C and other state-of-the-art methods. Moreover, our proposed method offers the JPEG compatibility at the same time.
“…(On the left is the original image, top two rows on the right are non-salient regions of reconstructed image, and two bottom rows on the right are salient ones. From left to right, the first row is original image, official implementation of JPEG XT profile A,B,C, the second row is Choi's method10 [10], Wei's method 21 [21], Feyiz's method 22 [22], and our proposed method, respectively. )Fig.…”
Section: Resultsmentioning
confidence: 99%
“…Their method is suitable to preserve local contrast and has lower computational complexity. Choi et al [10] proposed a novel method that is completely different from others. They generated the residual data in the DCT domain.…”
With wider luminance range than conventional low dynamic range (LDR) images, high dynamic range (HDR) images are more consistent with human visual system (HVS). Recently, JPEG committee releases a new HDR image compression standard JPEG XT. It decomposes an input HDR image into base layer and extension layer. The base layer code stream provides JPEG (ISO/IEC 10918) backward compatibility, while the extension layer code stream helps to reconstruct the original HDR image. However, this method does not make full use of HVS, causing waste of bits on imperceptible regions to human eyes. In this paper, a visual saliency-based HDR image compression scheme is proposed. The saliency map of tone mapped HDR image is first extracted, then it is used to guide the encoding of extension layer. The compression quality is adaptive to the saliency of the coding region of the image. Extensive experimental results show that our method outperforms JPEG XT profile A, B, C and other state-of-the-art methods. Moreover, our proposed method offers the JPEG compatibility at the same time.
“…We selected six metrics, which include mostly adopted metrics in the field of image coding research and additional metrics recently recommended by the JPEG working group [10], [11]. These comprise the following: 1) PSNR [12] calculated for color images [13]; 2) structural similarity index metric (SSIM) [14] focusing on the structural image difference; 3) multi-scale SSIM (MS-SSIM) [15] computing the SSIM over different resolutions to represent the quality at different resolutions and viewing conditions; 4)…”
Section: A Influence Of Proposed Progressive Mode On Jpeg Image Codimentioning
“…This technique achieved high quality image using final mapping decision method with low execution time. The discrete cosine transform technique was used to generate the residual data and created the backward compatible image coding method for HDR [26]. In Table 6 the LCGHDR method is compared with other methods and shows that this technique is process with low computational time.…”
Section: Comparison Analysismentioning
confidence: 99%
“…Computational time Meylan et al [22] 1.2153 Huo et al [23] 1.4100 Masia et al [24] 0.9955 Gwon Hwan An, et al [25] 0.6599 Seungcheol Choi, et al [26] 1.3505 HDRCloudSeg [27] 0.6241 LCGHDR 0.5826…”
The luminous value is high for many natural scenes, which causes loss of information and occurs in dark images. The High Dynamic Range (HDR) technique captures the same objects or scene for multiple times in different exposure and produces the images with proper illumination. This technique is used in the various applications such as medical imaging and observing the skylight, etc. HDR imaging techniques usually have the issue of lower efficiency due to capturing of multiple photos. In this paper, an efficient method is proposed for HDR imaging technique to achieve better performance and lower noise. The Luminance-Chrominance-Gradient High Dynamic Range (LCGHDR) method is proposed to obtain the proper luminous value of images. The same scenario is captured at different exposure are processed by the proposed method. Based on these feature values extracted from the different images and exposure fusion technique was developed that helps for the proper imaging. This experiment was evaluated and analyzed by comparing with the other methods, which showed the efficiency of the proposed method. This method needs only 124.594 seconds for the computation, while existing method need 139.869 seconds for the same number of images.
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