With the growing need for automated text recognition and image processing, we have explored techniques that enhance the accuracy of handwritten character recognition while simultaneously addressing image restoration challenges. Handwritten English Character Recognition leverages deep learning (DL) techniques to classify and accurately identify characters from scanned or photographed documents. A deep learning-based approach is employed to recognize the patterns in handwritten text, ensuring high precision in distinguishing between characters despite variances in writing styles. In addition to recognition, colorization of grayscale images has gained attention, where DL models predict and apply realistic colors to black-and-white images. The recognition process applies CNN (convolutional neural networks) for character identification.