# Computationally Efficient Robust Color Image Watermarking Using Fast Walsh Hadamard Transform
## 1 Introduction  
Now-a-days, internet and multimedia technologies have become part and parcel of the human life. The information shared on the world wide web (www) is proliferating day by day. Due to the recent advances in digital technologies, these contents can easily be copied, downloaded and manipulated [1]. Hacking and piracy turns out to be the byproduct of the digital revolutions. To prevent the anonymous manipulation of the digital contents and to protect the copyright, multimedia researchers introduced the copy deterrence mechanism called watermarks which are usually logos, stamps, Gaussian random patterns or pseudo noise sequences that are embedded in the media to be protected. Watermarking does not ensure that the watermarked image is completely secure because there can be intentional manipulations of the image (collusion, confusion and ownership deadlock), which actually try to destroy the embedded watermark or non-intentional manipulations like geometrical and signal processing operations (cropping, scaling, filtering, A/D conversion, etc.) [2]. The embedding algorithm should be designed in such a way that the embedded watermark survives the above mentioned attacks and can be extracted from the attacked image by the decoder. Such algorithms are known as robust and secure algorithms. The introduction of the watermarks should not degrade the perceptual quality of the original image. But as the amount of watermark content in the image to be protected (cover image) increases, the perceptual transparency shows significant reduction [3]. At the same time, more the amount of watermarks, the more robust will be the watermarked image against distortions and attacks. So the most important and desirable properties of the watermarks are perceptual quality and robustness even though there exists trade off among those properties. Along with that the good payload size, reduced false positive rate and information hiding capacity are also expected [4; 5]. Watermarks can be added to the digital image by modifying the pixel values as per the values of the watermarks which is known as spatial domain watermarking [6]. Alternately, by alteringthe transform domain values using common transforms like Discrete Cosine Transform (DCT) [3; 4], Discrete Wavelet Transform (DWT) [7; 8; 9], Fast Walsh Hadamard Transform (FWHT) [10; 11] or Fast Fourier Transform (FFT). Even though spatial domain techniques are simple to implement they are less robust against attacks [6]. On the other hand, frequency domain techniques show good robustness and perceptual quality but implementation is complex compared to spatial domain techniques [8]. Some researchers combine two transforms to achieve the advantages of both the transforms [12; 13; 14]. Watermarking has various applications like authentication, copyright protection, military and satellite applications, broadcast monitoring (ensuring the proper broadcast at the proper timing), transaction tracking/finger printing (finding out the source of leakage of multimedia signal), medical applications and many more [2; 3]. Based on the application, the properties should be set and accordingly the embedding and decoding algorithm should be modified. Among different ways of the watermarking models, the communication based model is the most important and widely used. From a communication point of view, watermarking system can be viewed as a process of communicating a message (watermark), through the fixed bandwidth channel (cover image), from the watermarking embedder to the watermarking decoder [1; 3; 4; 8]. Specifically, some researchers apply the concept of CDMA based communication system in which watermark will be spread using the orthogonal spreading code which is generated using the security key and is added to the selected frequency coefficients [7]. Decoding is usually done using correlation of the received image with the spreading codes.