Savitzky–Golay Filtering-Based Fusion of Multiple Exposure Images for High Dynamic Range Imaging

Abstract

The problem of compositing multiple exposure images has attracted lots of researchers, over the past years. It all began with the problem of High Dynamic Range (HDR) imaging, for capturing scenes with vast differences in their dynamic range. Fine details in all the areas in these scenes cannot be captured with one single exposure setting of the camera aperture. This leads to multiple exposure images with each image containing accurate representation of different regions dimly lit, well lit and brightly lit in the scenes. One can make a combined HDR image out of these multiple exposure shots. This combination of multiple exposure shots leads to an image of a higher dynamic range in a different image format which cannot be represented in the traditional Low Dynamic Range (LDR) formats. Moreover HDR images cannot be displayed in traditional display devices suitable for LDR. So these images have to undergo a process called as tone mapping for further converting them to be suitable enough to be represented on usual LDR displays. An approach based on Savitzky-Golay parametric filtering which preserves edges, is proposed which uses filtered multiple exposure images to generate the alpha matte coefficients required for fusing the input multiple exposure set. The coefficients generated in the proposed approach helps in retaining the weak edges and the fine textures which are lost as a result of the under and over exposures. The proposed approach is similar in nature to the bilateral filter-based compositing approach for multiple exposure images in the literature but it is novel, in exploring the possibility of compositing using a parametric filtering approach. The proposed approach performs the fusion in the LDR domain and the fused output can also be displayed using standard LDR image formats on standard LDR displays. A brief comparison of the results generated by the proposed method and various other approaches, including the traditional exposure fusion, tone mapping-based techniques and bilateral filter-based approach is presented where in the proposed method compares well and fares better in majority of the test cases.

DCT based Fusion of Variable Exposure Images for HDRI

“…Table 2. Performance parameters for the DCT-based Exposure Fusion and other state of the art approaches described in ( [1], [4], [13], [31], [32], [33], [34], [35], [36]and [37])…”

“…The DCT-based exposure fusion outputs are compared with the techniques described in ( [1], [4], [13], [31], [32], [33], [34], [35], [36] and [37] ). The PSNR and the SSIM scores are improved.…”

“…The PSNR, SSIM, IMMSE scores and the Q factor score [23] are tabulated in the table 2. [4], [13], [31], [32], [33], [34], [35], [36]and [37])…”

“…In addition we have transform domain approaches [4] and edge preserving Savitsky Golay filtering based approach [37].…”

Application of Dynamic Image Fusion Technology in Development of Innovation Capabilities of College Students Majoring in Art Design

“…The image processor is applied in simple scenarios and mainly for graphics rendering. It deals with data computing operations that are not dependent on each other and can be highly parallel, and that involve a huge amount of data [24,25]. The floating-point computing capacity of the image processor is much stronger and its bandwidth is much broader than those of the CPU, so it is easier to achieve parallelism, and the broad bandwidth ensures the timeliness of its data transmission [26].…”