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Image compression is dissimilar than compressing other unprocessed binary data. Obviously, general purpose compression techniques deliberated for raw binary data can be used to compress images, but the result is not the finest one, because of the variations in statistical property of image. Statistical properties of image must be completely exploit by encoders to obtained efficient image compression. The most popular transform coder was developed by the Joint Photographic Experts Group (JPEG), which utilizes fixed block size discrete cosine transform (DCT) to obtain image data decorrelation. With fixed block size DCT, JPEG has no independent control over quality and bit rate simultaneously. Human visual system is less sensitive to quantization noise in high-activity areas of an image than in low-activity areas. That means the threshold of visibility of quantization noise is higher in areas with details than in flat areas. this is the key, why not exploit human visual system's weakness to achieve much higher compression with good visual quality by hiding as much quantization noise in busy areas as possible. It is indeed possible by using DCT with varying block sizes and quantizing busy areas heavily and flat areas lightly. To apply variable block size DCT transform on an image, quad tree decomposition technique is commonly used. In quad tree decomposition technique a square block is divides in smaller blocks, if the difference between maximum and minimum pixel values exceeds a threshold. This threshold selection plays a very crucial role, because the independent selection of threshold value without considering the statistical properties of the input image, may lead to even worst compression characteristics. To address this difficulty, this paper proposes a novel optimum global thresholding based variable block size DCT coding for efficient image compression. The proposed method calculates the required threshold value for blocks decomposition using optimum global thresholding technique, which exploits the edge characteristics of the image. Comparison has been made with baseline fixed block size DCT coder by using mean square error (MSE), peak signal to noise ratio (PSNR) and compression ratio (CR) as criterions. It is shown that the variable block size DCT transform coding system using proposed optimum global thresholding technique has better MSE and highly improved PSNR and CR performance for all test images.