This paper proposes a simplified fractal image compression algorithm which is implemented on a block by block basis. This algorithm achieves a compression ratio of up to 1:10 with a peak signal to noise ratio (PSNR) as high as 35dB. The idea of the proposed algorithm is based on the segmentation of the image, first, into blocks to setup reference blocks. The image is then decomposed again into block ranges and a search process is carried out to find the reference blocks with best match. The transmitted or stored values, after compression, are the reference block values and the indices of the reference block that achieves the best match. If there is no match, the average value of the block range is transmitted or stored instead. It proposes also the effect of using the spiral architecture instead of square block decomposition and searching in fractal compression. Comparisons with other systems; conventional square, the proposed simplified fractal compression and the standard JPEG are introduced. We applied these types of fractal compression systems on a video sequence. Also the effect of using the fractal image compression algorithms in transform domain is proposed. The image is transferred firstly to the transform domain. The Discrete Cosine Transform (DCT) and Wavelet Transform (DWT) are used. After transformation takes place the fractal algorithms is applied. Comparisons between three fractal algorithms; conventional square, spiral, and a simplified fractal compression are proposed. The comparisons are repeated in the two cases of transformation. The discrete wavelet is used also in this paper to increase the compression ratio in case of using the conventional method. We used the two dimension discrete wavelet to increase the compression ratio of the block domain pool transmission. We decompose the block domain by wavelet decomposition to two levels which gives a compression ratio of block domain transmission as high as 1:16. The advantages of the proposed algorithm are the simplicity of computation. We found that the using of spiral architecture in fractal compression, the produced or decoded image and so the video sequence visual quality are better than that produced with conventional square method and the proposed simplified system at the same compression ratio but with longer time consumed. We found also that all types of fractal compression system give better quality than the standard JPEG. We found also that the decoded images in case of using the wavelet transform are the best. And the in case of using DCT the decoded images has bad qualities.