This paper proposes a novel exposure fusion technique based on Weighted Least Squares (WLS) optimization for weight map refinement. The method utilizes computationally simple texture features and color saturation measures to quickly generate weight maps that control the contribution from a set of multiexposure images. Instead of using intermediate HDR reconstruction and tone mapping steps, the method directly generates a well-exposed fused image suitable for display on conventional devices. The technique is well-suited for multifocus image fusion and has been compared with existing single and multiresolution exposure fusion techniques to demonstrate its effectiveness. The proposed method involves two-scale decomposition using anisotropic diffusion to separate sharp details and fine details across different exposure levels. A novel weight construction approach combines texture features and saturation measures to guide the fusion process. WLS filtering is used for weight refinement, and a fast sigmoid function is proposed for detail layer weight map generation, reducing computational complexity. The method's key contributions include: (1) a two-scale decomposition based on anisotropic diffusion for fast exposure fusion, (2) a novel weight construction approach that combines texture features and saturation measures, and (3) advantages such as ease of implementation, high quality of compositing, and detail layer enhancement without introducing artifacts. The method is evaluated against other exposure fusion, tone mapping, and multifocus image fusion techniques. Experimental results show that the proposed method effectively preserves texture details and local contrast while avoiding halos near strong edges. The method outperforms existing techniques in terms of quality, with results showing enhanced texture and edge features, better color appearance, and reduced artifacts. The method is computationally efficient and suitable for various consumer cameras entering the commercial market.This paper proposes a novel exposure fusion technique based on Weighted Least Squares (WLS) optimization for weight map refinement. The method utilizes computationally simple texture features and color saturation measures to quickly generate weight maps that control the contribution from a set of multiexposure images. Instead of using intermediate HDR reconstruction and tone mapping steps, the method directly generates a well-exposed fused image suitable for display on conventional devices. The technique is well-suited for multifocus image fusion and has been compared with existing single and multiresolution exposure fusion techniques to demonstrate its effectiveness. The proposed method involves two-scale decomposition using anisotropic diffusion to separate sharp details and fine details across different exposure levels. A novel weight construction approach combines texture features and saturation measures to guide the fusion process. WLS filtering is used for weight refinement, and a fast sigmoid function is proposed for detail layer weight map generation, reducing computational complexity. The method's key contributions include: (1) a two-scale decomposition based on anisotropic diffusion for fast exposure fusion, (2) a novel weight construction approach that combines texture features and saturation measures, and (3) advantages such as ease of implementation, high quality of compositing, and detail layer enhancement without introducing artifacts. The method is evaluated against other exposure fusion, tone mapping, and multifocus image fusion techniques. Experimental results show that the proposed method effectively preserves texture details and local contrast while avoiding halos near strong edges. The method outperforms existing techniques in terms of quality, with results showing enhanced texture and edge features, better color appearance, and reduced artifacts. The method is computationally efficient and suitable for various consumer cameras entering the commercial market.