In this paper, we introduce a ghost-free high dynamic range imaging algorithm to obtain ghost-free High Dynamic Range (HDR) images. The current HDR method based on multiple image fusion only works as long as there is no camera and object movement when capturing multiple LDR images with different exposure. To overcome this unrealistic condition, the proposed algorithm creates three LDR images from a single input image. For this purpose, a histogram separation method is proposed in the algorithm to generate three LDR images by stretching each separate histogram. An edge-preserving noise reduction technique is also proposed in the algorithm to suppress the noise that is amplified in the process of histogram stretching. Since the proposed algorithm automatically generates three LDR images from a single input image, ghost artifacts that are the result of relative motion between the camera and objects during different exposure times are removed from the HDR images. Therefore, the proposed algorithm can be applied to a mobile phone camera and a consumer compact camera to provide ghost artifact-free HDR images in the form of an integrated software application or post-processing. Keywords: high dynamic range imaging; HDR; LDR; Histogram stretching; Edge-Preserving Noise CancellationINTRODUCTIONCapturing real-world scenes becomes easier for non-experts as high-quality imaging devices are on the rise in the consumer electronics market. Three essential factors for capturing real-world scenes include; i) high spatial resolution, ii) true color reproduction and iii) high dynamic range (HDR). HDR imaging method has recently emerged in recent years and has played a significant role in bringing a new revolution to digital imaging [1]. While the human eye can recognize... the middle of the card... the basis for optimization of the [D] function", Edmonton University of Alberta, 1981.[11] J.N.Kapur, P. K Sahoo and AK C Wong , “A New Method for Image Thresholding Using Histogram Entropy, Computer Vision, and Image Processing,” vol ] R. A. Hummel, “Image Enhancement Using Histogram Transformation, Computer Graphics, and Image Processing,” vol.6, no.2, pp.184-195, 1977.[13] V. Maik and J. Paik, “Real-time image restoration for digital multiple focusing in a multiple-color filter aperture camera,” Optical Engineering, vol. 1-3), April 2010.[14] Jaehyun Im, Jaehwan Jeon, Monson H Hayes, “Single image-based ghost-free high dynamic range imaging using local histogram stretching and spatially adaptive denoising,” Consumer Electronics, IEEE Transaction, Vol.57, pp. 1478—1484, November 2011.