Video compression is the practice of reducing the size of video files while maintaining as much of the original quality as possible. To accomplish this, an application known as “codec” analyzes the video frame by frame, and breaks each frame down into square blocks known as “macroblocks”. The codec then analyzes each frame, checking for changes in the macroblocks. Areas where the macroblocks do not change for several frames in a row are noted and further analyzed. If the video compression codec determines that these areas can be removed from some of the frames, it does so, thus reducing the overall file size. There are two types of video compression: lossy and lossless. Lossy compression results in a lower file size, but also yields a loss in quality. Lossless compression, on the other hand, produces a less compressed file, but maintains the original quality. Videos and images are one of the most important approaches to represent some data. Now-a-days all the communication processes are working on such media. The main problem with this kind of media is its large size. Also, this large data contains a lot of redundant information. Compressing the video helps to reduce the size and thus saves the transmission bandwidth and storage space to achieve a high compression ratio while preserving the video quality. DWT (Discrete Wavelet Transform) and DCT (Discrete Cosine Transform) are the most common video compression techniques. DCT has high energy compaction and requires less computational resources, DWT on the other hand is a multiresolution transformation. But the compression ratio that can be achieved is low. The proposed method uses a Hybrid DWT-DCT algorithm on motion compensated frame by taking the advantages of both methods. The performance of the proposed method can be evaluated using compression ratio, PSNR (Peak Signal-to-Noice-Ratio) and mean square error.